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Abstract:

Method embodiments for performing a structured collection protocol by
utilizing a collection device comprise collecting one or more sampling
sets of biomarker data, wherein each sampling set comprises a sufficient
plurality of sampling instances recorded over a collection period. The
methods further include determining compliance with adherence criteria
for the sampling instances, wherein noncompliance with adherence criteria
is recorded as an adherence event, classifying sampling instances as
primary samples or secondary samples, wherein primary samples, which do
not have corresponding recorded adherence events, are sampling instances
utilized in the calculations performed by the processor that yield
therapy results for a diabetic person, and secondary samples are sampling
instances not utilized in the calculations, unless one or more secondary
samples are promoted to primary samples, and performing at least one
additional task if one or more sampling instances is a primary sample
with a corresponding recorded adherence event.

Claims:

1. A method of performing a structured collection protocol by utilizing a
collection device comprising a processor, wherein the method comprises:
collecting one or more sampling sets of biomarker data using the
collection device, wherein each sampling set comprises a sufficient
plurality of sampling instances recorded over a collection period,
wherein each sampling instance comprises a biomarker reading; determining
compliance with adherence criteria for the sampling instances of the
sampling set via the processor, wherein noncompliance with adherence
criteria is recorded as an adherence event; classifying sampling
instances as primary samples or secondary samples via the processor,
wherein primary samples, which do not have corresponding recorded
adherence events, are sampling instances utilized in calculations
performed by the processor that yield therapy results for a diabetic
person, and secondary samples are sampling instances not utilized in
calculations performed by the processor that yield therapy results for a
diabetic person, unless one or more secondary samples, which do not have
corresponding recorded adherence events, are promoted to primary samples;
and performing via the processor at least one additional task if one or
more sampling instances is a primary sample with a corresponding recorded
adherence event.

3. The method of claim 1 wherein the adherence criteria comprises
acceptance criteria, wherein the acceptance criteria require a biomarker
reading to be within an expected range.

4. The method of claim 3 wherein a biomarker reading outside of the
expected range is indicative of an adverse event.

5. The method of claim 1 further comprising classifying sampling
instances as tertiary samples for sampling instances which are not
utilized in the calculations of the structured collection protocol and
cannot be promoted to primary samples.

6. The method of claim 1 wherein the at least one additional task
comprises collecting at least one additional primary sample.

7. The method of claim 1 wherein the at least one additional task
comprises replacing via the processor one or more primary samples with
corresponding recorded adherence events with one or more secondary
samples if the secondary samples have no corresponding recorded adherence
events.

8. The method of claim 7 wherein the replacement of the primary samples
is performed automatically via the processor.

9. The method of claim 1 wherein the at least one additional task
comprises ignoring primary samples with corresponding recorded adherence
events and performing the calculations to yield therapy results to the
diabetic person based on primary samples in the sampling set, which do
not include corresponding recorded adherence events.

13. A method of performing a structured collection protocol by utilizing
a collection device comprising a processor, wherein the method comprises:
collecting a plurality of samples of biomarker data using the collection
device; classifying samples as critical if they are utilized in
calculations performed by the processor that yield therapy results for a
diabetic person, determining whether critical samples were collected
during a desired time window, wherein failure to collect a sample during
the time window is recorded as a missed sample; and replacing missed
critical samples with other samples recorded during the desired time
window.

14. A collection device configured to guide a diabetic person through a
structured collection protocol, comprising: a meter configured to measure
one or more selected biomarkers; a processor disposed inside the meter
and coupled to memory, wherein the memory comprises collection
procedures; and software having instructions that when executed by the
processor causes the processor to: instruct the diabetic person to
collect one or more sampling sets of biomarker data using the collection
device, wherein each sampling set comprises a sufficient plurality of
sampling instances recorded over a collection period, wherein each
sampling instance comprises a biomarker reading; determine compliance
with adherence criteria for the sampling instances of the sampling set
via the processor, wherein noncompliance with adherence criteria is
recorded as an adherence event; classify sampling instances as primary
samples or secondary samples via the processor, wherein primary samples,
which do not have corresponding recorded adherence events, are sampling
instances utilized in calculations performed by the processor that yield
therapy results for a diabetic person, and secondary samples are sampling
instances not utilized in calculations performed by the processor that
yield therapy results for a diabetic person, unless one or more secondary
samples, which do not have corresponding recorded adherence events, are
promoted to primary samples; and perform via the processor at least one
additional task if one or more sampling instances is a primary sample
with a corresponding recorded adherence event

16. The collection device of claim 14 wherein the adherence criteria
comprises acceptance criteria, wherein the acceptance criteria require a
biomarker reading to be within an expected range.

17. The collection device of claim 14 wherein a biomarker reading outside
of the expected range is indicative of an adverse event.

18. The collection device of claim 14 wherein sampling instances are
classified as tertiary samples for sampling instances which are not
utilized in the calculations of the structured collection protocol and
cannot be promoted to primary samples.

19. The collection device of claim 14 wherein the at least one additional
task is the collection of at least one additional primary sample.

20. The collection device of claim 14 wherein the at least one additional
task is the replacement of one or more primary samples with corresponding
recorded adherence events with one or more secondary samples if the
secondary samples have no corresponding recorded adherence events.

21. The collection device of claim 20 wherein the replacement of the
primary samples is automatic.

22. The collection device of claim 14 wherein the additional task is the
termination of the structured collection protocol.

23. A method of performing a structured collection protocol by utilizing
a collection device comprising a processor, wherein the method comprises:
collecting one or more sampling sets of biomarker data using the
collection device, wherein each sampling set comprises a sufficient
plurality of sampling instances recorded over a collection period,
wherein each sampling instance comprises a biomarker reading; determining
compliance with adherence criteria for the sampling instances of the
sampling set via the processor, wherein noncompliance with adherence
criteria is recorded as an adherence event; classifying sampling
instances as primary samples or secondary samples via the processor; and
performing via the processor at least one additional task if one or more
primary samples is recorded with a corresponding recorded adherence
event, wherein the at least one additional task is calculated by the
processor based on the adherence event as well as on the classification
of the sampling instance.

24. The method of claim 23 wherein primary samples, which do not have
corresponding recorded adherence events, are sampling instances utilized
in an assessment of the structured collection protocol and secondary
samples are sampling instances not utilized for the assessment performed
by the processor, unless one or more secondary samples, which do not have
corresponding recorded adherence events, are promoted to primary samples.

25. The method of claim 23 wherein the calculations of the structured
collection protocol performed by the processor yield therapy results for
a diabetic person.

26. The method of claim 23 wherein sampling instances comprising the same
contextual data belong to the same sampling set.

27. The method of claim 26 wherein the contextualized data of the primary
sample, which is replaced by the secondary sample, at least partially
identical with the contextualized data of the secondary sample

28. The method of claim 23 wherein primary samples, which have
corresponding recorded adherence events are replaced by secondary
samples, which do not have corresponding recorded adherence events, and
are promoted to primary samples.

29. The method of claim 23 wherein the contextualized data of the primary
sample, which is replaced by the secondary sample, is at least partially
identical with the contextualized data of the secondary sample

Description:

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application is a continuation-in-part of U.S. patent
application Ser. No. 12/643,415 filed Dec. 21, 2009 (WP 26405), which
claims priority to U.S. Provisional Application Ser. No. 61/140,270 filed
Dec. 23, 2008. The present application is also a continuation-in-part of
U.S. patent application Ser. No. 12/818,310 filed Jun. 18, 2010 (WP
26287), which is a continuation-in-part of U.S. patent application Ser.
No. 12/643,338 filed Dec. 21, 2009 (WP 25378), which also claims priority
to U.S. Provisional Application Ser. No. 61/140,270 filed Dec. 23, 2008.
All of the above applications are incorporated by reference herein in
their entirety.

TECHNICAL FIELD

[0002] Embodiments of the present invention relate generally to devices
collecting physiological information, and particularly to a system and
method managing the implementation, execution, data collection, and data
analysis of a structured collection procedure or protocol running on a
portable, hand-held collection device.

BACKGROUND

[0003] A disease which is long lasting or which reoccurs often is defined
typically as a chronic disease. Known chronic diseases include, among
others, depression, compulsive obsession disorder, alcoholism, asthma,
autoimmune diseases (e.g. ulcerative colitis, lupus erythematosus),
osteoporosis, cancer, and diabetes mellitus. Such chronic diseases
require chronic care management for effective long-term treatment. After
an initial diagnosis, one of the functions of chronic care management is
then to optimize a patient's therapy of the chronic disease.

[0004] In the example of diabetes mellitus, which is characterized by
hyperglycemia resulting from inadequate insulin secretion, insulin
action, or both, it is known that diabetes manifests itself differently
in each person because of each person's unique physiology that interacts
with variable health and lifestyle factors such as diet, weight, stress,
illness, sleep, exercise, and medication intake. Biomarkers are patient
biologically derived indicators of biological or pathogenic processes,
pharmacologic responses, events or conditions (e.g., aging, disease or
illness risk, presence or progression, etc.). For example, a biomarker
can be an objective measurement of a variable related to a disease, which
may serve as an indicator or predictor of that disease. In the case of
diabetes mellitus, such biomarkers include measured values for glucose,
lipids, triglycerides, and the like. A biomarker can also be a set of
parameters from which to infer the presence or risk of a disease, rather
than a measured value of the disease itself. When properly collected and
evaluated, biomarkers can provide useful information related to a medical
question about the patient, as well as be used as part of a medical
assessment, as a medical control, and/or for medical optimization.

[0005] For diabetes, clinicians generally treat diabetic patients
according to published therapeutic guidelines such as, for example,
Joslin Diabetes Center & Joslin Clinic, Clinical Guideline for
Pharmacological Management of Type 2 Diabetes (2007) and Joslin Diabetes
Center & Joslin Clinic, Clinical Guideline for Adults with Diabetes
(2008). The guidelines may specify a desired biomarker value, e.g., a
fasting blood glucose value of less than 100 mg/dl, or the clinician can
specify a desired biomarker value based on the clinician's training and
experience in treating patients with diabetes. However, such guidelines
do not specify biomarker collection procedures for parameter adjustments
to support specific therapies used in optimizing a diabetic patient's
therapy. Subsequently, diabetic patients often must measure their glucose
levels with little structure for collection and with little regard to
lifestyle factors. Such unstructured collections of glucose levels can
result in some biomarker measurements lacking interpretative context,
thereby reducing the value of such measurements to clinicians and other
such health care providers helping patients manage their disease.

[0006] A patient with a chronic disease may be asked by different
clinicians at various times to perform a number of collections in an
effort to diagnose a chronic disease or to optimize therapy. However,
these requests to perform such collections according to a schedule may
overlap, be repeats, run counter to each other and/or provide a burden on
the patient such that the patient may avoid any further attempts to
diagnose their chronic disease or to optimize therapy.

[0007] In addition, if a requesting clinician does not evaluate the
patient properly to see if the schedule of requested collections is
possible and/or whether parameters for the collections are suitable
and/or acceptable for the patient, having useful results from such
collections may be unlikely. Still further, if there has not been enough
suitable data collected to complete the requested collections, such that
the data collected is helpful towards addressing the medical question
and/or the interests of the clinician, such a request may waste the time
and effort of the clinician and the patient as well as the consumables
used to perform the collections. Again, such failure may discourage the
patient from seeking further therapy advice.

[0008] Moreover, prior art collection devices used in facilitating a
schedule of collections provide limited guidance, if any at all, and
simple reminders of a collection event. Such prior art devices typically
need to be programmed manually by the either clinician or the patient, in
which to govern the collection schedule. Such limited guidance and
functionality provided by prior art collection devices can also further
discourage the patient from seeking any future optimization of their
therapy as performing another collection procedure in this manner may be
viewed as being laborious by the patient, thereby leaving such
optimization to simply guessing.

SUMMARY

[0009] It is against the above background that embodiments of the present
invention present a system and method managing the implementation,
execution, data collection, and data analysis of a prospective structured
collection procedure running on a portable, hand-held collection device.
Embodiments of the present invention can be implemented on various
collection devices, such as a blood glucose measuring device (meter) that
has the capability to accept and run thereon one or more collection
procedures and associated meter-executable scripts according to the
present invention. These collection procedures in one embodiment can be
generated on a computer or any device capable of generating a collection
procedure.

[0010] In one embodiment, a method of performing a structured collection
protocol by utilizing a collection device comprising a processor is
provided. The method comprises collecting one or more sampling sets of
biomarker data using the collection device, wherein each sampling set
comprises a sufficient plurality of sampling instances recorded over a
collection period, and wherein each sampling instance comprises a
biomarker reading. The method also comprises determining compliance with
adherence criteria for the sampling instances of the sampling set via the
processor, wherein noncompliance with adherence criteria is recorded as
an adherence event, and classifying sampling instances as primary samples
or secondary samples via the processor, wherein primary samples, which do
not have corresponding recorded adherence events, are sampling instances
utilized in calculations performed by the processor that yield therapy
results for a diabetic person, and secondary samples are sampling
instances not utilized in calculations performed by the processor that
yield therapy results for a diabetic person, unless one or more secondary
samples, which do not have corresponding recorded adherence events, are
promoted to primary samples. The method also comprises performing via the
processor at least one additional task if one or more sampling instances
is a primary sample with a corresponding recorded adherence event.

[0011] In another embodiment, the method may be performed on a collection
device configured to guide a diabetic person through a structured
collection protocol. The collection devices comprises a meter configured
to measure one or more selected biomarkers, a processor disposed inside
the meter and coupled to memory, wherein the memory comprises collection
procedures; and software having instructions to be executed by the
processor.

[0012] In yet another embodiment, another method of performing a
structured collection protocol by utilizing a collection device
comprising a processor is provided. The method comprises collecting a
plurality of samples of biomarker data using the collection device,
classifying samples as critical if they are utilized in calculations
performed by the processor that yield therapy results for a diabetic
person, and determining whether critical samples were collected during a
desired time window, wherein failure to collect a sample during the time
window is recorded as a missed sample. The method further comprises
replacing missed critical samples with other samples recorded during the
desired time window.

[0013] According to another embodiment, a method of performing a
structured collection protocol by utilizing a collection device
comprising a processor is provided. The method comprises collecting one
or more sampling sets of biomarker data using the collection device,
wherein each sampling set comprises a sufficient plurality of sampling
instances recorded over a collection period, wherein each sampling
instance comprises a biomarker reading, determining compliance with
adherence criteria for the sampling instances of the sampling set via the
processor, wherein noncompliance with adherence criteria is recorded as
an adherence event, classifying sampling instances as primary samples or
secondary samples via the processor; and performing via the processor at
least one additional task if one or more primary samples is recorded with
a corresponding recorded adherence event, wherein the at least one
additional task is calculated by the processor based on the adherence
event as well as on the classification of the sampling instance.

[0014] These and other advantages and features of the invention disclosed
herein, will be made more apparent from the description, drawings and
claims that follow.

BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The following detailed description of the embodiments of the
present invention can be best understood when read in conjunction with
the following drawings, where like structure is indicated with like
reference numerals.

[0016]FIG. 1 is a diagram showing a chronic care management system for a
diabetes patient and a clinician along with others having an interest in
the chronic care management of the patient according to an embodiment of
the present invention.

[0017] FIGS. 2 and 2A are diagrams showing embodiments of a system
suitable for implementing a structured collection according to an
embodiment of the present invention.

[0018] FIG. 3 shows a block diagram of a collection device embodiment
according to the present invention.

[0019]FIG. 4 shows a depiction in tabular format of a data record
embodiment created from using a structured collection on the collection
device of FIG. 3 according to the present invention.

[0020] FIG. 5A depicts a method of creating a structured collection
procedure for a medical use case and/or question according to an
embodiment of the present invention.

[0021] FIGS. 5B and 5C show parameters defining a structured collection
procedure and factors which can be considered to optimize a patient's
therapy using the structured collection procedure, respectively,
according to one or more embodiments of the present invention.

[0022] FIGS. 6A, 6B, 6C, 6D, and 6E show various structured collection
procedures embodiments defined according to the present invention.

[0023]FIG. 7A depicts a structured collection for diagnostic or therapy
support of a patient with a chronic disease according to an embodiment of
the present invention.

[0024] FIG. 7B conceptually illustrates one example of a pre-defined
structured collection procedure, and a method for customizing the
pre-defined structured collection procedure according to an embodiment of
the present invention.

[0025] FIG. 8A shows a method for performing a structured collection
procedure according to an embodiment of the present invention.

[0026] FIGS. 8B and 8C show a method of implementing a structured
collection procedure via a graphical user interface provided on a
collection device according to an embodiment of the present invention.

[0027]FIG. 9 shows a method for performing a structured collection
procedure to obtain contextualized biomarker data from a patient
according to another embodiment of the present invention.

[0028] FIG. 10A depicts non-contextualized and contextualized data.

[0029] FIG. 10B depicts a typical collection procedure according to an
embodiment of the present invention.

[0030] FIG. 11 depicts a diagram of accepted contextualized data
intermingled with non-acceptable contextualized data according to an
embodiment of the present invention.

[0031]FIG. 12 depicts elements of software according to an embodiment of
the present invention.

[0032] FIGS. 13 and 14 depict a collection procedure execution method
according to an embodiment of the present invention.

[0033]FIG. 15 shows a method of providing diabetes diagnostics and
therapy support according to a use case embodiment of the present
invention.

[0034] FIGS. 16, 17, and 18 depict different screen shots of a graphical
user interface according to an embodiment of the present invention.

[0035] FIGS. 19A-19D shows flow charts depicting structure collection
protocols for optimizing the titration of insulin according to
embodiments of the present invention.

[0036] FIG. 20 is a flow chart depicting testing methods for optimizing
the titration of insulin according to embodiments of the present
invention.

DETAILED DESCRIPTION

[0037] The present invention will be described below relative to various
illustrative embodiments. Those skilled in the art will appreciate that
the present invention may be implemented in a number of different
applications and embodiments and is not specifically limited in its
application to the particular embodiments depicted herein. In particular,
the present invention will be discussed below in connection with diabetes
management via sampling blood, although those of ordinary skill will
recognize that the present invention could be modified to be used with
other types of fluids or analytes besides glucose, and/or useful in
managing other chronic diseases besides diabetes.

[0038] As used herein with the various illustrated embodiments described
below, the follow terms include, but are not limited to, the following
meanings.

[0039] The term "biomarker" can mean a physiological variable measured to
provide data relevant to a patient such as for example, a blood glucose
value, an interstitial glucose value, an HbA1c value, a heart rate
measurement, a blood pressure measurement, lipids, triglycerides,
cholesterol, and the like.

[0040] The term "contextualizing" can mean documenting and interrelating
conditions that exists or will occur surrounding a collection of a
specific biomarker measurement. Preferably, data about documenting and
interrelating conditions that exists or will occur surrounding a
collection of a specific biomarker are stored together with the collected
biomarker data and are linked to it. In particular, a further assessment
of the collected biomarker data takes into account the data about
documenting and interrelating conditions so that not only the data as
such are evaluated but also the link between data to which it is
contextualized. The data about documenting and interrelating conditions
can include for example information about the time, food and/or exercises
which occurs surrounding a collection of a specific biomarker measurement
and/or simultaneously thereto. For example, the context of a structured
collection procedure according in an embodiment to the present invention
can be documented by utilizing entry criterion for verifying a fasting
state with the user before accepting a biomarker value during a Basal
titration optimization focused testing procedure.

[0041] The term "contextualized biomarker data" can mean the information
on the interrelated conditions in which a specific biomarker measurement
was collected combined with the measured value for the specific
biomarker. In particular, the biomarker data are stored together with the
information on the interrelated conditions under which a specific
biomarker measurement was collected and are linked thereto.

[0042] The term "criteria" can mean one or more criterions, and can be at
least one or more of a guideline(s), rule(s), characteristic(s), and
dimension(s) used to judge whether one or more conditions are satisfied
or met to begin, accept, and/or end one or more procedural steps,
actions, and/or values.

[0043] The term "adherence" can mean that a person following a structured
collection procedure performs requested procedural steps appropriately.
For example, the biomarker data should be measured under prescribed
conditions of the structured collection procedure. If then the prescribed
conditions are given for a biomarker measurement, the adherence is
defined as appropriate. For examples, the prescribed conditions are time
related conditions and/or exemplarily can include eating of meals, taking
a fasting sample, eating a type of meal with a requested window of time,
taking a fasting sample at a requested time, sleeping a minimum amount of
time, and the like. The adherence can be defined as appropriate or not
appropriate for a structured collection procedure or a single data point
in particular of a contextualized biomarker data. Preferably, the
adherence can be defined as appropriate or not appropriate by a range of
a prescribed condition(s) or by a selectively determined prescribed
condition(s). Moreover the adherence can be calculated as a rate of
adherence describing in which extent the adherence is given for a
structured collection procedure or a single data point in particular of a
contextualized biomarker data.

[0044] The term "adherence event" can mean when a person executing a
structured collection procedure fails to perform a procedural step. For
example, if a person did not collect data when requested by the
collection device, the adherence is determined as not appropriate
resulting in an adherence event. In another example, adherence criteria
could be a first criterion for the patient to fast 6 hours and a second
criterion for collecting a fasting bG value at a requested time. In this
example, if the patient provides the bG sampling at the requested time
but fasted only 3 hours before providing, then although the second
adherence criterion is met, the first adherence criterion is not, and
hence an adherence event for the first criterion would occur.

[0045] The term "violation event" is a form of an adherence event in which
the person executing the structured collection (testing) procedure
(protocol) does not administer a therapeutic at a recommended time, does
administer a recommended amount, or both.

[0046] The term "adherence criterion" can include adherence and can also
mean a basis for comparison (e.g., assessment) of a measured value, a
value related to a measured value and/or a calculated value with a
defined value or defined range of the value wherein based on the
comparison data are accepted with approval and positive reception.
Adherence criterion can take into account time related values and/or
adherence in one embodiment, but also can take into account noise in
other embodiments, and the like. Furthermore, adherence criterion can be
applied to contextualized biomarker data so that a biomarker data is
accepted depending on a comparison of the contextualized data about
documenting and interrelating conditions that exists or occurs
surrounding the collection of the specific biomarker. Adherence criterion
can be akin to a sanity check for a given piece of information, or group
of information. In one embodiment, the single data point/information or
group of data or information is rejected if the accepted criterion is not
fulfilled. In particular, such rejected data are then not used for
further calculations which are used to provide a therapy recommendation.
Mainly the rejected data are only used to assess the adherence and/or to
trigger automatically at least one further action. For example, such a
triggered action prompts the user then to follow a structured collection
procedure or a single requested action so that based on that action the
adherence criterion can be fulfilled.

[0047] The term "data event request" can mean an inquiry for a collection
of data at a single point in space-time defined by a special set of
circumstances, for example, defined by time-related or not time-related
events.

[0048] The term "decentralized disease status assessment" can mean a
determination of the degree or extent of progression of a disease
performed by using a biomarker measurement of interest to deliver a value
without sending a sample to a laboratory for assessment.

[0049] The term "medical use case or question" can mean at least one or
more of a procedure, situation, condition, and/or question providing an
uncertainty about the factuality of existence of some medical facts,
combined with a concept that is not yet verified but that if true would
explain certain facts or phenomena. Medical use case or question can be
already deposited and stored in the system so that the user can select
between different medical use cases or questions. Alternatively, the
medical use case or question can be defined by the user itself.

[0050] The terms "focused", "structured", and "episodic" are used herein
interchangeably with the term "testing" and can mean a predefined
sequence in which to conduct the testing.

[0051] The terms "software" and "program" may be used herein
interchangeably.

[0052]FIG. 1 shows a chronic care management system 10 for a diabetes
patient(s) 12 and a clinician(s) 14 along with others 16 having an
interest in the chronic care management of the patient 12. Patient 12,
having dysglycemia, may include persons with a metabolic syndrome,
pre-diabetes, type 1 diabetes, type 2 diabetes, and gestational diabetes.
The others 16 with an interest in the patient's care may include family
members, friends, support groups, and religious organizations all of
which can influence the patient's conformance with therapy. The patient
12 may have access to a patient computer 18, such as a home computer,
which can connect to a public network 50 (wired or wireless), such as the
internet, cellular network, etc., and couple to a dongle, docking
station, or device reader 22 for communicating with an external portable
device, such as a portable collection device 24. An example of a device
reader is shown in the manual "Accu-Chek® Smart Pix Device Reader
User's Manual" (2008) available from Roche Diagnostics.

[0053] The collection device 24 can be essentially any portable electronic
device that can function as an acquisition mechanism for determining and
storing digitally a biomarker value(s) according to a structured
collection procedure, and which can function to run the structured
collection procedure and the method of the present invention. Greater
details regarding various illustrated embodiments of the structured
collection procedure are provided hereafter in later sections. In one
embodiment, the collection device 24 can be a self-monitoring blood
glucose meter 26 or a continuous glucose monitor 28. An example of a
blood glucose meter is the Accu-Chek® Active meter, and the
Accu-Chek® Aviva meter described in the booklet "Accu-Chek® Aviva
Blood Glucose Meter Owner's Booklet (2007), portions of which are
disclosed in U.S. Pat. No. 6,645,368 B1 entitled "Meter and method of
using the meter for determining the concentration of a component of a
fluid" assigned to Roche Diagnostics Operations, Inc., which is hereby
incorporated by reference. An example of a continuous glucose monitor is
shown in U.S. Pat. No. 7,389,133 "Method and device for continuous
monitoring of the concentration of an analyte" (Jun. 17, 2008) assigned
to Roche Diagnostics Operations, Inc., which is hereby incorporated by
reference.

[0054] In addition to the collection device 24, the patient 12 can use a
variety of products to manage his or her diabetes including: test strips
30 carried in a vial 32 for use in the collection device 24; software 34
which can operate on the patient computer 18, the collection device 24, a
handheld computing device 36, such as a laptop computer, a personal
digital assistant, and/or a mobile phone; and paper tools 38. Software 34
can be pre-loaded or provided either via a computer readable medium 40 or
over the public network 50 and loaded for operation on the patient
computer 18, the collection device 24, the clinician computer/office
workstation 25, and the handheld computing device 36, if desired. In
still other embodiments, the software 34 can also be integrated into the
device reader 22 that is coupled to the computer (e.g., computers 18 or
25) for operation thereon, or accessed remotely through the public
network 50, such as from a server 52.

[0055] The patient 12 can also use, for certain diabetes therapies,
additional therapy devices 42 and other devices 44. Additionally, therapy
devices 42 can include devices such as an ambulatory infusion pump 46, an
insulin pen 48, and a lancing device 51. An example of an ambulatory
insulin pump 46 include but not limited thereto the Accu-Chek® Spirit
pump described in the manual "Accu-Chek® Spirit Insulin Pump System
Pump User Guide" (2007) available from Roche Diabetes Care. The other
devices 44 can be medical devices that provide patient data such as blood
pressure, fitness devices that provide patient data such as exercise
information, and elder care device that provide notification to care
givers. The other devices 44 can be configured to communicate with each
other according to standards planned by Continua® Health Alliance.

[0056] The clinicians 14 for diabetes are diverse and can include e.g.,
nurses, nurse practitioners, physicians, endocrinologists, and other such
health care providers. The clinician 14 typically has access to a
clinician computer 25, such as a clinician office computer, which can
also be provided with the software 34. A healthcare record system 27,
such as Microsoft® HealthVault® and Google® Health, may also be
used by the patient 12 and the clinician 14 on computers 18, 25 to
exchange information via the public network 50 or via other network means
(LANs, WANs, VPNs, etc.), and to store information such as collection
data from the collection device 24 to an electronic medical record of the
patient e.g., EMR 53 (FIG. 2A) which can be provided to and from computer
18, 25 and/or server 52.

[0057] Most patients 12 and clinicians 14 can interact over the public
network 50 with each other and with others having computers/servers 52.
Such others can include the patient's employer 54, a third party payer
56, such as an insurance company who pays some or all of the patient's
healthcare expenses, a pharmacy 58 that dispenses certain diabetic
consumable items, a hospital 60, a government agency 62, which can also
be a payer, and companies 64 providing healthcare products and services
for detection, prevention, diagnosis and treatment of diseases. The
patient 12 can also grant permissions to access the patient's electronic
health record to others, such as the employer 54, the payer 56, the
pharmacy 58, the hospital 60, and the government agencies 62 via the
healthcare record system 27, which can reside on the clinician computer
25 and/or one or more servers 52. Reference hereafter is also made to
FIG. 2.

[0058] FIG. 2 shows a system embodiment suitable for implementing a
structured collection according to an embodiment of the present
invention, which in another embodiment can be a part of the chronic care
management system 10 and communicate with such components, via
conventional wired or wireless communication means. The system 41 can
include the clinician computer 25 that is in communication with a server
52 as well as the collection device 24. Communications between the
clinician computer 25 and the server 52 can be facilitated via a
communication link to the public network 50, to a private network 66, or
combinations thereof. The private network 66 can be a local area network
or a wide are network (wired or wireless) connecting to the public
network 50 via a network device 68 such as a (web) server, router, modem,
hub, and the likes.

[0059] In one embodiment, the server 52 can be a central repository for a
plurality of structured collection procedures (or protocols) 70a, 70b,
70c, 70d, in which the details of a few exemplary structured collection
procedures are provided in later sections. The server 52, as well as the
network device 68, can function also as a data aggregator for completed
ones of the structured collection procedures 70a, 70b, 70c, 70d.
Accordingly, in such an embodiment, data of a completed collection
procedure(s) from a collection device of the patient 12 can then be
provided from the server 52 and/or network device 68 to the clinician
computer 25 when requested in response to a retrieval for such patient
data.

[0060] In one embodiment, one or more of the plurality of structured
collection procedures 70a, 70b, 70c, 70d on the server 52 can be provided
over the public network 50, such as through a secure web interface 55
(FIG. 2A, showing another embodiment of the system 41) implemented on the
patient computer 18, the clinician computer 25, and/or the collection
device 24. In another embodiment, the clinician computer 25 can serve as
the interface (wired or wireless) 72 between the server 52 and the
collection device 24. In still another embodiment, the structured
collection procedures 70a, 70b, 70c, 70d, as well as software 34, may be
provided on a computer readable medium 40 and loaded directed on the
patient computer 18, the clinician computer 25, and/or the collection
device 24. In still another embodiment, the structured collection
procedures 70a, 70b, 70c, 70d may be provided pre-loaded (embedded) in
memory of the collection device 24. In still other embodiments,
new/updated/modified structured collection procedures 70a, 70b, 70c, 70d
may be sent between the patient computer 18, the clinician computer 25,
the server 52 and/or the collection device 24 via the public network 50,
the private network 66, via a direct device connection (wired or
wireless) 74, or combinations thereof. Accordingly, in one embodiment the
external devices e.g., computer 18 and 25, can be used to establish a
communication link 72, 74 between the collection device 24 and still
further electronic devices such as other remote Personal Computer (PC),
and/or servers such as through the public network 50, such as the
Internet and/or other communication networks (e.g., LANs, WANs, VPNs,
etc.), such as private network 66.

[0061] The clinician computer 25, as a conventional personal
computer/workstation, can include a processor 76 which executes programs,
such as software 34, and such as from memory 78 and/or computer readable
medium 40. Memory 78 can include system memory (RAM, ROM, EEPROM, etc.),
and storage memory, such as hard drives and/or flash memory (internal or
external). The clinician computer 25 can also include a display driver 80
to interface a display 82 with the processor 76, input/output connections
84 for connecting user interface devices 86, such as a keyboard and mouse
(wired or wireless), and computer readable drives 88 for portable memory
and discs, such as computer readable medium 40. The clinician computer 25
can further include communication interfaces 90 for connections to the
public network 50 and other devices, such as collection device 24 (wired
or wireless), and a bus interface 92 for connecting the above mentioned
electronic components to the processor 76. Reference hereafter is now
made to FIG. 3.

[0062] FIG. 3 is a block diagram conceptually illustrating the portable
collection device 24 depicted in FIG. 2. In the illustrated embodiment,
the collection device 24 can include one or more microprocessors, such as
processor 102, which may be a central processing unit comprising at least
one more single or multi-core and cache memory, which can be connected to
a bus 104, which may include data, memory, control and/or address buses.
The collection device 24 can include the software 34, which provides
instruction codes that causes a processor 102 of the device to implement
the methods of the present invention that are discussed hereafter in
later sections. The collection device 24 may include a display interface
106 providing graphics, text, and other data from the bus 104 (or from a
frame buffer not shown) for display on a display 108. The display
interface 106 may be a display driver of an integrated graphics solution
that utilizes a portion of main memory 110 of the collection device 24,
such as random access memory (RAM) and processing from the processor 102
or may be a dedicated graphic processing unit. In another embodiment, the
display interface 106 and display 108 can additionally provide a touch
screen interface for providing data to the collection device 24 in a
well-known manner.

[0063] Main memory 110 in one embodiment can be random access memory
(RAM), and in other embodiments may include other memory such as a ROM,
PROM, EPROM or EEPROM, and combinations thereof. In one embodiment, the
collection device 24 can include secondary memory 112, which may include,
for example, a hard disk drive 114 and/or a computer readable medium
drive 116 for the computer readable medium 40, representing for example,
at least one of a floppy disk drive, a magnetic tape drive, an optical
disk drive, a flash memory connector (e.g., USB connector, Firewire
connector, PC card slot), etc. The drive 116 reads from and/or writes to
the computer readable medium 40 in a well-known manner. Computer readable
medium 40, represents a floppy disk, magnetic tape, optical disk (CD or
DVD), flash drive, PC card, etc. which is read by and written to by the
drive 116. As will be appreciated, the computer readable medium 40 can
have stored therein the software 34 and/or structured collection
procedures 70a, 70b, 70c, and 70d as well as data resulting from
completed collections performed according to one or more of the
collection procedures 70a, 70b, 70c, and 70d.

[0064] In alternative embodiments, secondary memory 112 may include other
means for allowing the software 34, the collection procedures 70a, 70b,
70c, 70d, other computer programs or other instructions to be loaded into
the collection device 24. Such means may include, for example, a
removable storage unit 120 and an interface connector 122. Examples of
such removable storage units/interfaces can include a program cartridge
and cartridge interface, a removable memory chip (e.g., ROM, PROM, EPROM,
EEPROM, etc.) and associated socket, and other removable storage units
120 (e.g. hard drives) and interface connector 122 which allow software
and data to be transferred from the removable storage unit 120 to the
collection device 24.

[0065] The collection device 24 in one embodiment can include a
communication module 124. The communication module 124 allows software
(e.g., the software 34, the collection procedures 70a, 70b, 70c, and 70d)
and data (e.g., data resulting from completed collections performed
according to one or more of the collection procedures 70a, 70b, 70c, and
70d) to be transferred between the collection device 24 and an external
device(s) 126. Examples of communication module 124 may include one or
more of a modem, a network interface (such as an Ethernet card), a
communications port (e.g., USB, Firewire, serial, parallel, etc.), a PC
or PCMCIA slot and card, a wireless transceiver, and combinations
thereof. The external device(s) 126 can be the patient computer 18, the
clinician computer 25, the handheld computing devices 36, such as a
laptop computer, a personal digital assistance (PDA), a mobile (cellular)
phone, and/or a dongle, a docking station, or device reader 22. In such
an embodiment, the external device 126 may provided and/or connect to one
or more of a modem, a network interface (such as an Ethernet card), a
communications port (e.g., USB, Firewire, serial, parallel, etc.), a
PCMCIA slot and card, a wireless transceiver, and combinations thereof
for providing communication over the public network 50 or private network
66, such as with the clinician computer 25 or server 52. Software and
data transferred via communication module 124 can be in the form of wired
or wireless signals 128, which may be electronic, electromagnetic,
optical, or other signals capable of being sent and received by
communication module 124. For example, as is known, signals 128 may be
sent between communication module 124 and the external device(s) 126
using wire or cable, fiber optics, a phone line, a cellular phone link,
an RF link, an infrared link, other communications channels, and
combinations thereof. Specific techniques for connecting electronic
devices through wired and/or wireless connections (e.g. USB and
Bluetooth, respectively) are well known in the art.

[0066] In another embodiment, the collection device 24 can be used with
the external device 132, such as provided as a handheld computer or a
mobile phone, to perform actions such as prompt a patient to take an
action, acquire a data event, and perform calculations on information. An
example of a collection device combined with such an external device 126
provided as a hand held computer is disclosed in U.S. patent application
Ser. No. 11/424,757 filed Jun. 16, 2006 entitled "System and method for
collecting patient information from which diabetes therapy may be
determined," assigned to Roche Diagnostics Operations, Inc., which is
hereby incorporated by reference. Another example of a handheld computer
is shown in the user guide entitled "Accu-Chek® Pocket Compass
Software with Bolus Calculator User Guide" (2007) available from Roche
Diagnostics.

[0067] In the illustrative embodiment, the collection device 24 can
provide a measurement engine 138 for reading a biosensor 140. The
biosensor 140, which in one embodiment is the disposable test strip 30
(FIG. 1), is used with the collection device 24 to receive a sample such
as for example, of capillary blood, which is exposed to an enzymatic
reaction and measured by electrochemistry techniques, optical techniques,
or both by the measurement engine 138 to measure and provide a biomarker
value, such as for example, a blood glucose level. An example of a
disposable test strip and measurement engine is disclosed in U.S. Patent
Pub. No. 2005/0016844 A1 "Reagent stripe for test strip" (Jan. 27, 2005),
and assigned to Roche Diagnostics Operations, Inc., which is hereby
incorporated by reference. In other embodiments, the measurement engine
138 and biosensor 140 can be of a type used to provide a biomarker value
for other types of sampled fluids or analytes besides or in addition to
glucose, heart rate, blood pressure measurement, and combinations
thereof. Such an alternative embodiment is useful in embodiments where
values from more then one biomarker type are requested by a structured
collection procedure according to the present invention. In still another
embodiment, the biosensor 140 may be a sensor with an indwelling
catheter(s) or being a subcutaneous tissue fluid sampling device(s), such
as when the collection device 24 is implemented as a continuous glucose
monitor (CGM) in communication with an infusion device, such as pump 46
(FIG. 1). In still another embodiments, the collection device 24 can be a
controller implementing the software 34 and communicating between the
infusion device (e.g., ambulatory insulin pump 46 and electronic insulin
pen 48) and the biosensor 140.

[0068] Data, comprising at least the information collected by the
biosensor 140, is provided by the measurement engine 138 to the processor
102 which may execute a computer program stored in memory 110 to perform
various calculations and processes using the data. For example, such a
computer program is described by U.S. patent application Ser. No.
12/492,667, filed Jun. 26, 2009, titled "Method, System, and Computer
Program Product for Providing Both an Estimated True Mean Blood Glucose
Value and Estimated Glycated Hemoglobin (HbA1C) Value from Structured
Spot Measurements Of Blood Glucose," and assigned to Roche Diagnostics
Operations, Inc., which is hereby incorporated by reference. The data
from the measurement engine 138 and the results of the calculation and
processes by the processor 102 using the data is herein referred to as
self-monitored data. The self-monitored data may include, but not limited
thereto, the glucose values of a patient 12, the insulin dose values, the
insulin types, and the parameter values used by processor 102 to
calculate future glucose values, supplemental insulin doses, and
carbohydrate supplement amounts as well as such values, doses, and
amounts. Such data along with a date-time stamp 169 for each measured
glucose value and administered insulin dose value is stored in a data
file 145 of memory 110 and/or 112. An internal clock 144 of the
collection device 24 can supply the current date and time to processor
102 for such use.

[0069] The collection device 24 can further provide a user interface 146,
such as buttons, keys, a trackball, touchpad, touch screen, etc. for data
entry, program control and navigation of selections, choices and data,
making information requests, and the likes. In one embodiment, the user
interface 146 can comprises one or more buttons 147, 149 for entry and
navigation of the data provided in memory 110 and/or 112. In one
embodiment, the user can use one or more of buttons 147, 149 to enter
(document) contextualizing information, such as data related to the
everyday lifestyle of the patient 12 and to acknowledge that prescribed
tasks are completed. Such lifestyle data may relate to food intake,
medication use, energy levels, exercise, sleep, general health conditions
and overall well-being sense of the patient 12 (e.g., happy, sad, rested,
stressed, tired, etc.). Such lifestyle data can be recorded into memory
110 and/or 112 of the collection device 24 as part of the self-monitored
data via navigating through a selection menu displayed on display 108
using buttons 147, 149 and/or via a touch screen user interface provided
by the display 108. It is to be appreciated that the user interface 146
can also be used to display on the display 108 the self monitored data or
portions thereof, such as used by the processor 102 to display measured
glucose levels as well as any entered data.

[0070] In one embodiment, the collection device 24 can be switched on by
pressing any one of the buttons 147, 149 or any combination thereof. In
another embodiment, in which the biosensor 140 is a test-strip, the
collection device 24 can be automatically switched on when the test-strip
is inserted into the collection device 24 for measurement by the
measurement engine 138 of a glucose level in a sample of blood placed on
the test-strip. In one embodiment, the collection device 24 can be
switched off by holding down one of the buttons 147, 149 for a
pre-defined period of time, or in another embodiment can be shut down
automatically after a pre-defined period of non-use of the user interface
146.

[0071] An indicator 148 can also be connected to processor 102, and which
can operate under the control of processor 102 to emit audible, tactile
(vibrations), and/or visual alerts/reminders to the patient of daily
times for bG measurements and events, such as for example, to take a
meal, of possible future hypoglycemia, and the likes. A suitable power
supply 150 is also provided to power the collection device 24 as is well
known to make the device portable.

[0072] As mentioned above previously, the collection device 24 may be
pre-loaded with the software 34 or by provided therewith via the computer
readable medium 40 as well as received via the communication module 124
by signal 128 directly or indirectly though the external device 132
and/or network 50. When provided in the latter matter, the software 34
when received by the processor 102 of the collection device 24 is stored
in main memory 110 (as illustrated) and/or secondary memory 112. The
software 34 contains instructions, when executed by the processor 102,
enables the processor to perform the features/functions of the present
invention as discussed herein in later sections. In another embodiment,
the software 34 may be stored in the computer readable medium 40 and
loaded by the processor 102 into cache memory to cause the processor 102
to perform the features/functions of the invention as described herein.
In another embodiment, the software 34 is implemented primarily in
hardware logic using, for example, hardware components such as
application specific integrated circuits (ASICs). Implementation of the
hardware state machine to perform the feature/functions described herein
will be apparent to persons skilled in the relevant art(s). In yet
another embodiment, the invention is implemented using a combination of
both hardware and software.

[0073] In an example software embodiment of the invention, the methods
described hereafter can be implemented in the C++ programming language,
but could be implemented in other programs such as, but not limited to,
Visual Basic, C, C#, Java or other programs available to those skilled in
the art. In still other embodiment, the program 34 may be implemented
using a script language or other proprietary interpretable language used
in conjunction with an interpreter. Reference hereafter is also made to
FIG. 4.

[0074]FIG. 4 depicts in tabular form a data file 145 containing data
records 152 of self-monitored data 154 resulting from a structured
collection procedure according to an embodiment of the present invention.
The data records 152 (e.g., rows) along with the self-monitoring data 154
(e.g., various one of the columns) can also provide associated therewith
contextual information 156 (e.g., other various ones of the columns as
well as via row and column header information). Such contextual
information 156 can be collected either automatically, such as for
example via input received automatically from the measurement engine, the
biosensor, and/or any one of the other devices, or via input received
from the user interface which was manually enter by the patient in
response to a collection request (e.g., a question displayed by the
processor 102 on the display 108) during the structured collection
procedure. Accordingly, as such contextual information 156 can be
provided with each data record 152 in one embodiment, such information is
readily available to a physician and no further collection of such
information is necessarily needed to be provided again by the patient
either manually or orally after completing the structured collection
procedure. In another embodiment, if such contextual information 156
and/or additional contextual information is collected after completion of
a structured collection procedure according to the present invention,
such information may be provided in the associated data file 145 and/or
record 152 at a later time such as via one of the computers 18, 25. Such
information would then be associated with the self-monitored data in the
data file 145, and thus would not need to be provided again orally or
manually. Such a process in the latter embodiment may be needed in the
situation where the structured collection procedure is implemented as or
partly as a paper tool 38 which is used with a collection device
incapable of running the software 34 implementing such a structured
collection procedure.

[0075] It is to be appreciated that the date file 145 (or portions
thereof, such as only the self-monitored data 154) can be sent/downloaded
(wired or wireless) from the collection device 24 via the communication
module 124 to another electronic device, such the external device 132
(PC, PDA, or cellular telephone), or via the network 50 to the clinician
computer 25. Clinicians can use diabetes software provided on the
clinician computer 25 to evaluate the received self-monitored data 154 as
well as the contextual information 156 of the patient 12 for therapy
results. An example of some of the functions which may be incorporated
into the diabetes software and which is configured for a personal
computer is the Accu-Chek® 360 Diabetes Management System available
from Roche Diagnostics that is disclosed in U.S. patent application Ser.
No. 11/999,968 filed Dec. 7, 2007, titled "METHOD AND SYSTEM FOR SETTING
TIME BLOCK," and assigned to Roche Diagnostics Operations, Inc., which is
hereby incorporated by reference.

[0076] In one embodiment, the collection device 24 can be provided as
portable blood glucose meter, which is used by the patient 12 for
recording self-monitored data comprising insulin dosage readings and spot
measured glucose levels. Examples of such bG meters as mentioned above
previously include but are not limited to, the Accu-Chek® Active
meter and the Accu-Chek® Aviva system both by Roche Diagnostics, Inc.
which are compatible with the Accu-Chek® 360° Diabetes
management software to download test results to a personal computer or
the Accu-Chek® Pocket Compass Software for downloading and
communication with a PDA. Accordingly, it is to be appreciated that the
collection device 24 can include the software and hardware necessary to
process, analyze and interpret the self monitored data in accordance with
predefined flow sequences (as described below in detail) and generate an
appropriate data interpretation output. In one embodiment, the results of
the data analysis and interpretation performed upon the stored patient
data by the collection device 24 can be displayed in the form of a
report, trend-monitoring graphs, and charts to help patients manage their
physiological condition and support patient-doctor communications. In
other embodiments, the bG data from the collection device 24 may be used
to generated reports (hardcopy or electronic) via the external device 132
and/or the patient computer 18 and/or the clinician computer 25.

[0077] The collection device 24 can further provide the user and/or his or
her clinician with at least one or more of the possibilities comprising:
a) editing data descriptions, e.g. the title and description of a record;
b) saving records at a specified location, in particular in
user-definable directories as described above; c) recalling records for
display; d) searching records according to different criteria (date,
time, title, description etc.); e) sorting records according to different
criteria (e.g., values of the bG level, date, time, duration, title,
description, etc.); f) deleting records; g) exporting records; and/or h)
performing data comparisons, modifying records, excluding records as is
well known.

[0078] As used herein, lifestyle can be described in general as a pattern
in an individual's habits such as meals, exercise, and work schedule. The
individual additionally may be on medications such as insulin therapy or
orals that they are required to take in a periodic fashion. Influence of
such action on glucose is implicitly considered by the present invention.

[0079] It is to be appreciated that the processor 102 of the collection
device 24 can implement one or more structured collection procedures 70
provided in memory 110 and/or 112. Each structured collection procedure
70 in one embodiment can be stand-alone software, thereby providing the
necessary program instructions which when executed by the processor 102
causes the processor to perform the structure collection procedure 70 as
well as other prescribed functions. In other embodiments, each structured
collection procedure 70 can be part of the software 34, and can be then
be selectively executed by the processor 102 either via receiving a
selection from a menu list provided in the display 108 from the user
interface 146 in one embodiment or via activation of a particular user
interface, such as a structured collection procedure run mode button (not
shown) provided to the collection device 24 in another embodiment. It is
to be appreciated that the software 34, likewise, provides the necessary
program instructions which when executed by the processor 102 causes the
processor to perform the structure collection procedure 70 as well as
other prescribed functions of the software 34 discussed herein. One
suitable example of having a selectable structured collection procedure
provided as a selectable mode of a collection meter is disclosed by in
U.S. patent application Ser. No. 12/491,523, filed Jun. 25, 2009, titled
"Episodic Blood Glucose Monitoring System With An Interactive Graphical
User Interface And Methods Thereof," assigned to Roche Diagnostics
Operations, Inc., which is hereby incorporated by reference.

[0080] In still another embodiment, a command instruction can be sent from
the clinician computer 25 and received by the processor 102 via the
communication module 124, which places the collection device 24 in a
collection mode which runs automatically the structured collection
procedure 70. Such a command instruction may specify which of the one or
more structured collection procedures to run and/or provide a structured
collection procedure to run. In still another embodiment, a list of
defined medical use cases or medical questions can be presented on the
display 108 by the processor 102, and a particular structured collection
procedure 70 can be automatically chosen by the processor 102 from a
plurality of structured collection procedures (e.g., procedures 70a, 70b,
70c, and 70d) depending on the selection of the defined medical use cases
or medical questions received by the processor 102 via the user interface
146.

[0081] In still another embodiment, after selection, the structured
collection procedure(s) 70 can be provided through the computer readable
medium e.g., 40 and loaded by the collection device 24, downloaded from
computer 18 or 25, the other device(s) 132, or server 52. Server 52, for
example, may be a healthcare provider or company providing such
pre-defined structured collection procedures 70 for downloading according
to a selected defined medical use case or question. It is to be
appreciated that the structured collection procedure(s) 70 may be
developed by a healthcare company (e.g. company 64) and implemented via
the public network 50 through a webpage and/or made available for
downloading on server 52, such as illustrated in FIG. 2. In still other
embodiments, notices that a new structured collection procedure 70 is
available for use on the collection device 24 to help address a
particular use case/medical question that a user (e.g., healthcare
provider and patient) may have can be provided in any standard fashion,
such for via postal letters/cards, email, text messaging, tweets, and the
likes.

[0082] In some embodiments, as mentioned above previously, a paper tool 38
can perform some of the functions provided by the diabetes software 34.
An example of some of the functions which may be incorporated into the
diabetes software 34 and which is configured as a paper tool 38 is the
Accu-Chek® 360 View Blood Glucose Analysis System paper form
available from Roche Diagnostics also disclosed in U.S. patent
application Ser. No. 12/040,458 filed Feb. 29, 2007 entitled "Device and
method for assessing blood glucose control," assigned to Roche Diagnostic
Operations, Inc., which is hereby incorporated by reference.

[0083] In still another embodiment, the software 34 can be implemented on
the continuous glucose monitor 28 (FIG. 1). In this manner, the
continuous glucose monitor 28 can be used to obtain time-resolved data.
Such time-resolved data can be useful to identify fluctuations and trends
that would otherwise go unnoticed with spot monitoring of blood glucose
levels and standard HbA1c tests. Such as, for example, low overnight
glucose levels, high blood glucose levels between meals, and early
morning spikes in blood glucose levels as well as how diet and physical
activity affect blood glucose along with the effect of therapy changes.

[0084] In addition to collection device 24 and software 34, clinicians 14
can prescribe other diabetes therapy devices for patients 12 such as an
ambulatory insulin pump 46 as well as electronically based insulin pen 48
(FIG. 1). The insulin pump 46 typically includes configuration software
such as that disclosed in the manual "Accu-Chek® Insulin Pump
Configuration Software" also available from Disetronic Medical Systems
AG. The insulin pump 46 can record and provide insulin dosage and other
information, as well as the electronically based insulin pen 48, to a
computer, and thus can be used as another means for providing biomarker
data as requested by the structured collection procedure 70 (FIG. 2)
according to the present invention.

[0085] It is to be appreciated that, and as mentioned above previously,
one or more of the method steps discussed hereafter can be configured as
a paper tool 38 (FIG. 1), but preferably all the method steps are
facilitated electronically on system 41 (FIG. 2) or on any electronic
device/computer, such as collection device 24, having a processor and
memory as a program(s) residing in memory. As is known, when a computer
executes the program, instructions codes of the program cause the
processor of the computer to perform the method steps associated
therewith. In still other embodiments, some or all of the method steps
discussed hereafter can be configured on computer readable medium 40
storing instruction codes of a program that, when executed by a computer,
cause the processor of the computer to perform the method steps
associated therewith. These method steps are now discussed in greater
detail hereafter with reference made to FIGS. 5A and 5B.

[0086] Create a Structured Collection Procedure

[0087] FIG. 5A depicts a method 200 of creating a structured collection
procedure 70 illustrated by FIG. 5B for a medical use case or question
which may be implemented in any one of the above described devices 18,
24, 25, 26, 28, 36, 52 as stand alone software, as part of the diabetes
software 34 or portions there of as part of paper tool 38. In step 202, a
medical use case or question, hereafter referred to generally as use
case(s), is selected and/or can be defined. It is to be appreciated that
a use case may be, for example, one selected from the following medical
use cases or questions: a desire to know the effects of eating a
particular food; a desire to know the best time to take medication before
and/or after with a meal; and a desire to know the effects of exercise on
bG levels. Other use cases may be questions concerning finding a
diagnosis, how best to initialize therapy for a patient, finding a
determination of status of a patient disease progression, finding the
best ways to optimize a patient therapy, and the like. Still other
examples can be providing such structured collection procedures 70 which
can be used to help address medical questions regarding fasting blood
glucose, pre-prandial glucose values, postprandial glucose values, and
the like. Other medical questions can be to control the biomarker in a
predefined context, to optimize the biomarker in a predefined context,
related to therapy onset, type of therapy, oral mono-therapy, oral
combination therapy, insulin therapy, lifestyle therapy, adherence to
therapy, therapy efficacy, insulin injection or inhalation, type of
insulin, split of insulin in basal and bolus, and the likes. For example,
medical questions regarding oral mono-therapy and oral combination could
include those involving sulfonylureas, biguanides, thiazolidinediones,
alpha-glucosidase inhibitors, meglitinides, dipeptidyl peptidase IV
inhibitors, GLP-1 analogs, taspoglutide, PPAR dual alpha/gamma agonists,
aleglitazar. The selected use case can be assigned to a medical use case
parameter 220 depicted in FIG. 5B.

[0088] In step 204, the situation or problem surrounding the selected use
case can be defined. This can be accomplished via looking at all the
factors which may affect a change in the use case. For example, in the
use case of desiring to know how best to optimize a patient's therapy
some factors to look at may include stress, menstrual cycle, pre-dawn
effect, background insulin, exercise, bolus timing with respect to a
meal, basal rate, insulin sensitivity, post-prandial behavior, and the
like such as shown by FIG. 5c.

[0089] In step 206, a determination can be made as to what kinds of
analysis can be used to address or shed light on the situation or the
problem. Such analysis may be, for example, selected from the following:
evaluating the change in fasting blood glucose (FPG) values over the
course of the collection procedure 70, monitoring one or more particular
value over the duration of the collection procedure 70, determining an
insulin to carbohydrate (I:C) ratio, determining insulin sensitivity,
determining best time for administering a drug with respect to another
variable, such as meal(s), and the like. In step 208, a sampling group
determination can be made as to which information has to be collected,
such as what biomarker(s) and the context(s) in which the biomarkers
shall be collected, as well as when this information needs to be
collected to conduct the analysis. For example, the sampling group can be
defined as a string of data objects, each of which consists of: target
type, e.g., time based which can use a target time (e.g., used for an
alerting feature), a lower time window bound, an upper time window bound,
etc., or data based which defines a data type (single, aggregate, or
formula), the conditions for accepting the data (e.g., none, below a
value, above a value, a formula, etc.), the type of collection (e.g.,
user input, sensor, data, etc.), as well as any reminder screen text
(e.g., static, and/or dynamic in both formatting and value insertion) for
each collection. The result of this process is a schedule of collection
events 222 (FIG. 5B). Next in step 210, the manner in which each or a
group of the schedule of collection events 222 is/are to be conducted in
order to be useful for addressing the situation or problem of the
selected use case is then determined. This results in one or more
adherence criterions 224. In addition to and/or instead of the manner for
performing a collection, the adherence criterion(s) 224 may also be based
on one or more biomarker values falling into a pre-defined range or is
equal to a certain pre-defined value. In other embodiments, the adherence
criterion(s) can be a formula (s) which uses a biomarker datum or group
of such data to determine if the resulting value falls into the
pre-defined range or is equal to a certain pre-defined value.

[0090] For example, adherence criteria 224 can describe the parameters
around the events 237 that the patient 12 needs to perform such as tests
within a certain window, fasting for a given amount of time, sleeping for
a given amount of time, exercise, low stress, not menstruating, etc. As
such, an adherence criterion 224 can establish the context of the
information about to be provided. Adherence criteria 224 can also be used
as mentioned above previously in another context to provide an assessment
of whether the data is acceptable, and when used in such a context may be
referenced to as "acceptance" criteria. For example, before a sample is
taken, the adherence criteria 224 can establish whether steps leading up
to taking of the sample are accomplished. For example, the processor 102
in response to a request 240 displays the question, "Have you been
fasting for the last 8 hours?", wherein a "Yes" response received by the
processor via the user interface 146 meets the adherence criterion 224
for this step. In another example, after the sample is taken, the
processor 102 can assess the received data for reasonableness using other
adherence (acceptance) criterion(s). For example, based on prior data, a
fasting bG sample should be between 120-180 mg/dl, but the received value
was of 340 mg/dl, and thus fails such adherence (acceptance) criteria
since being out of the predefined range for an acceptable value. In such
an example, an adherence event 242 occurs wherein the processor 102 could
prompt for an additional sample. In such a case, if the re-sampling fails
too (i.e., not between 120-180 mg/dl), the assessment provided by the
processor 102 is that the patient 12 has not fasted, and thus the
processor 102 as instructed by the adherence criterion upon a failing of
the re-sampling extend automatically the events 237 in the schedule of
events 222 accordingly.

[0091] Next in step 212, the condition(s) and context(s) in which the
schedule of events 222 is to be started and ended can be determined. This
results in one or more entry criterions 226 and exit criterions 228 being
provided for the schedule of events 222 as well as possibly for a group
of other schedule of events to which the schedule of events 222 belongs
if providing a package of structured collection procedures, e.g.,
procedures 70a, 70b, 70c, and 70d, which may run concurrently and/or
sequentially one after the other.

[0092] For example, the one or more entry criterions 226 can be used to
determine whether the patient meets the conditions to use the collection
procedure by the processor 102 checking that, for example, the patient 12
meets the entry criterion 226 based on current age being in a range,
HbA1c being in a range, that the patient has a particular disease, has
had the disease over a minimum period of time, has a Body Mass Index
(BMI) in a range, had a Fasting Plasma Glucose (FPG) in a range, had a
particular drug sensitivity, is taking a particular drug, taking a
particular drug dosage, meets one or more prerequisites of another
structured collection procedure, has completed one or more of another
structured collection procedure, does not have one or more particular
pre-conditions, e.g., pregnant, not fasting, or contraindications, e.g.,
feeling ill, feverish, vomiting, etc., and combinations thereof. Entry
criterion 226 can also initiate the schedule of events 222 by an
initiation event such as a time of day, a time of week, meal, taking a
meal with a time offset, exercise, and exercise with a time offset, use
of a therapeutic drug, use of a therapeutic drug with time offset,
physiological circumstances, biomarker range, and biomarker within a
predetermined range calculated as an offset from a prior biomarker value.
Example of a physiological circumstance can be that entry criterion will
be met to start a structured collection procedure when a pre-determined
number of a physiological event, e.g., hyperglycemia, hypoglycemia, a
certain temperature at a certain of day, and the like, occur within a
pre-defined amount of time, e.g., hours, day, weeks, etc. Accordingly,
the entry criterion can be used to support the use of need to met
prerequisites, indications for usage, and/or contraindications for usage.
For example, an entry criterion 226 could define a prerequisite condition
which in order for the structure collection procedure 70 to run an
Insulin Sensitivity optimization, the processor 102 must verify first
that a structured collection procedure for a Basal titration is completed
and/or has a desired result and/or as well as another structured
collection procedure for an insulin to carbohydrate ratio is completed
and/or has a desired result. In another example, an entry criterion 226
could define a condition which needs to meet certain indications for
usage in which certain structured collection procedures could provide
segregated uses for diabetics who are Type 1 vs. Type 2 as well as types
of structure collection procedures which can be used to titrate for
specific drugs. In another example, the entry criterion 226 could define
a condition which needs to meet certain contraindications for usage, in
which for example, certain structured collection procedures 70 will not
run if the patient 12 is pregnant, sick, etc.

[0093] Examples of the one or more exit criterions 228 can be based on the
processor 102 determining that a particular value is reached, that a mean
average of the primary samples values are in a range, that a particular
event(s) and/or condition(s) have or have not occurred, and combinations
thereof. Other conditions when the procedure may stop can include adverse
events such as a hypoglycemic event, the patient is sick, the patient
undergoes a therapy change, etc. Additional detail may also by provided
by the processor 102 on the display 108 to the patient 12 based on what
the specific exit criterion has been met. For example, in one example, if
the patient 12 measures a glucose value indicating hypoglycemia, upon
exiting the procedure, the processor 102 run automatically another
alternative procedure which instructs the patient 12 to ingest
carbohydrates and measure his blood glucose value every half an hour
until the blood glucose exceeds 120 mg/dL. For this alternative
procedure, the patient 12 can also be requested by the processor 102 to
document his meals, activity, stress, and other relevant details to
ensure that the conditions that led to hypoglycemia are recorded. The
patient 12 may also be instructed by the processor 102 to contact the
clinician 14 in this and other such special cases as deemed fit. Exit
criteria can also include, for example, criterion for ending such as
exiting after a successful completion, or exiting after an indeterminate
completion, such as expiration of a predetermined timeout (logistical
end), e.g., no result after n days, where n=1 to 365 days, or by
termination e.g., exit with unsuccessful termination due to a fail-safe.
It is to be appreciated that the structured collection procedure 70 can
also be defined to end automatically not only based on meeting the exit
criterion 228, but also when the patient 12 fails to perform a request to
an acceptable level of compliance and/or when a patient physiological
state has changed such that the patient is should not carry out the
schedule of events 222, thereby failing adherence criteria 224, wherein
the adherence event 242 is to end the structured collection procedure.

[0094] In step 214, guidance 230 for the user during collection can be
determined as well as any options 232 for customizing the collection. For
example, for guidance 230, the clinician 14 can use a default list of
messages, or tailor messages to guide the patient 12 during execution of
the collection procedure 70. As an example, one message could be provided
on a successful data acquisition (i.e., meets the adherence criteria 224)
would read, "Thank you. Your next scheduled measurement is at 1230 pm."
Alarms, such as provided by indicator 148, can also be associated with
the collection procedure 70 that remind the patient 12 to take a
measurement and can include a snooze functionality should the patient 12
need additional time to conduct the measurement. The snooze functionality
as well as other device features are discussed further in later sections.

[0095] The result of steps 208-214 is the structured collection procedure
70 being created in step 216 which associates together the use case
parameter 220, the scheduled of events 222, the adherence criterion(s)
224, the entry criterion(s) 226, the exit criterion(s) 228, guidance 230,
and the options 232. In one embodiment, at the time of generating a
collection procedure 70, the clinician 14 also generates printed material
that explains to the patient the following aspects (at a minimum): the
purpose of the collection procedure 70 and expected ideal outcome, i.e.,
setting a goal for the collection procedure 70; the collection procedure
70 design and the number of measurements needed; the entry criteria 226
that the patient 12 must satisfy before initiating the collection
procedure 70 and before taking each reading; and the exit criteria 228
under which the patient 12 should cease to continue the collection
procedure 70. Such printed material as well as the guidance 230 that can
be provided during the execution of the collection procedure 70 ensures
that the patient is fully aware of why the data collection procedure is
being carried out.

[0096] Examples of the structured collection procedure 70 may be, for
example, a structured collection procedure for determining an
insulin-to-carbohydrate ratio, for determining bolus timing in respect to
meal start, and for determining an exercise equivalent to ingested
carbohydrates. In step 218, the structured collection procedure 70 is
then made available for implementation and use in the system 41, such as
in any of the above discussed manners mentioned with regards to FIGS. 1,
2, and 3. A structured collection procedure 70 accordingly may be
provided via the above process, such as by either the medical community
or healthcare companies 64, to help the clinician 14 address and/or
investigate a defined medical use case or problem.

[0097] FIG. 5B shows the interactions of the parameters 222, 224, 226, and
228 of the structured collection procedure 70 for obtaining
contextualized biomarker data from a diabetic patient to address a
medical use case upon which the structured collection procedure is based.
As mentioned above, the use case parameter 220 may be provided to
identify the medical use case or question to which the parameters 222,
224, 226, and 228 address. For example, the processor 76 of the clinician
computer 25, the processor 102 of the collection device 24, and/or the
server 52 may read the medical use case parameters 220 from a plurality
of structured collection procedures 70a, 70b, 70c, 70d (FIG. 2), such as
provided on these devices and/or within the system 41, and provide a list
of the available structured collection procedures, such as on the display
82 of the clinician computer 25 or the display 108 of the collection
device 24. Additionally, the clinician computer 25, the patient computer
18, and/or the server 52 can use the medical use case parameter 220 for
locating/sorting/filtering such structured collection procedures
according to a medical use case(s).

[0098] As mentioned above, the entry criterion(s) 226 establishes the
requirements for initiating the structured collection procedure 70 to
obtain patient data which includes biomarker data, particularly,
collected in a predefined context. In one embodiment, the processor 102
of the collection device 24 can use the entry criterion(s) 226 to
determine when an associated structured collection procedure 70 is
appropriate for the patient's physiological context and to ensure that
all of the necessary inputs to the associated structured collection
procedure have been established. Therefore, it is to be appreciated that
the start date and/time of a structured collection procedure may
dynamically change automatically by the processor 102 of the collection
device 24 if the predefined condition(s) of the entry criterion(s) 226 is
not satisfied. Accordingly, until the entry criterion 226 is satisfied,
the start date and/time of the associated structured collection procedure
70 can be at some unknown time in the future.

[0099] For example, in one embodiment, a structured collection procedure
70 can be chosen automatically by the processor 102 from a plurality of
structured collection procedures 70a, 70b, 70c, 70d, such as provided in
memory 110 of the collection device 24, memory of the computer 18, 25
and/or from server 52, based on satisfying the condition(s) of a defined
entry criterion 226 for an associated structured collection procedure.
For example, in one embodiment, a first structured collection procedure,
such as procedure 70d, is useful for showing trends in blood glucose
levels ("bG Level Trending"). Therefore, an entry criterion 226 for the
first structured collection procedure 70d may be for the patient to have
a bG level mean which has elevated over a defined period (e.g., a past
number of days, weeks, and months from the current date) above a certain
pre-defined rate. For a second structured collection procedure, such as
procedure 70a, its entry criteria 226 may require a particular number of
bG measurement for a pre-breakfast measurement over a defined period
(e.g., a past number of days, weeks, months, from the current date) being
below a pre-defined bG value. In such an example, the processor 102 upon
start up in one embodiment when commanded, such as via input received via
the user interface in another embodiment, or at a scheduled time as
programmed by the software 34 in still another embodiment, can run
through the various entry criteria 226 provided by the various structured
collection procedures 70a and 70d that are, for example, provided in
memory 110 of the collection device 24 and determine whether the stated
condition(s) for the entry criteria 226 of a particular structured
collection procedure 70 is satisfied. In this example, the processor 102
determines that the historical data from past measurements in memory 110
indicate that the patient's bG level mean has been elevating, and that
the entry criterion 226 for the first collection procedure 70d has been
met, but not the entry criteria for the second collection procedure 70a.
In this example, the processor 102 then automatically selects and starts
the first structured collection procedure 70d based on the
above-mentioned analysis.

[0100] It is also to be appreciated that the use of the entry criterion
226 can help to reduce the misallocation of medical expenses by assuring
that the indications of use for the structured collection procedure 70
have been met before starting the schedule of collection events 222. The
entry criterion 226 as well can help assure that any requests to perform
multiple structured collection procedures do not overlap if incompatible,
are not unnecessary repeats of each other, or provide a significant
burden on the patient. In this manner, many of the noted problems in
which a patient may avoid any further attempts to diagnose their chronic
disease or to optimize therapy can be both addressed and avoided
automatically by the processor 102 of the collection device 24 via use of
the entry criterion 226.

[0101] As shown by FIG. 5B, the entry criteria 226 can include context
specific entry criterion 234, procedure specific entry criterion 236, and
combination thereof. Examples of context specific entry criterion 234 can
include one or more variables to identify meals, low blood glucose
events, insulin type and dosage, stress, and the like. In another
example, the context specific entry criterion 234 can be defined such as
in the form of a specific question(s), to which the processor 102
requires a specific answer to be received from patient via input from the
user interface 146. For example, the processor 102 in executing the entry
criterion 226 may display on the display 108 the question of whether the
patient is willing and able to perform the structured collection
procedure 70 over the required period. If the patient responses
affirmatively via the user interface 146, then the entry criterion 226
has been satisfied and the processor 102 continues automatically with
performing the collection events 237 according to the their associated
timing as defined in the structured collection procedure 70. If the
patient responses in the negative to the displayed question, then the
processor 102 will not continue with the structured collection procedure
70, and may for example, re-schedule the asking of such a question to a
future time, such as if designated by an options parameter.

[0102] Examples of procedure specific entry criterion 236 can include one
or more variables to identify disease state, disease status, selected
therapy, parameter prerequisites, insulin to carbohydrate ratio prior to
testing insulin sensitivity, incompatible collection procedures, and the
like. The procedure specific entry criterion 236 can be defined such that
the processor 102 will continue automatically with the structured
collection procedure 70 with one of three initiators--the patient 12, the
clinician 14, or data, e.g., if the condition(s) of the entry criterion
226 is satisfied. For example, the procedure specific entry criterion 236
can be satisfy if the clinician 14 has prescribed the structured
collection procedure 70, such as via an authorized user entering via the
user interface 146 a valid password to unlock the particular structured
collection procedure for use, in one embodiment. In another embodiment,
the clinician 14 can send the password or an authorization code from
clinician computer 25 and/or server 52 to the collection device 24 which
prescribes (authorizes) the collection procedure 70 for use by the
patient 12 on the collection device 24. It is to be appreciated that one
or more structured collection procedure 70 can be provided in memory 110
of the collection device 24 which cannot be used by the patient 12, and
which can be also hidden from being viewed on the display 108, such as in
a selection list, by the patient until authorized by the clinician 14.

[0103] The procedure specific entry criterion 236 can be satisfy by a user
for example, by the user selecting a particular structured collection
procedure 70 from a listing of structured collection procedures 70a, 70b,
70c, 70d provided on the display 108. An example of a data initiated
procedure for criterion 236 would be that a biomarker measurement(s)
provided to the processor 102 indicates a certain condition which must
have occurred or be present in order for the entry criteria 226 for the
particular structured collection procedure to be satisfied. Such a
condition, for example, can be the occurrence of a single event, such as
a severe hypoglycemic event, or a series of events, such as hypoglycemic
events within a given, a predetermined time frame, such as in 24 hours
from a start time, in one week from a start time, etc, a calendar
date-time, and the like.

[0104] Accordingly, the entry criteria 226 can be a single criterion or
multiple criteria that establish context and/or condition of the
patient's physiology that are relevant to the medical use case being
addressed by the structured collection procedure 70. In another
embodiment, the entry criteria 226 can be assessed after patient data has
been collected, such as, on historical patient data.

[0105] The schedule of events 222 specifies one or more events 237 which
each comprises at least one or more variables defining a performance time
238, the guidance 230 to perform the event, requests 240 for patient
actions, which may include a request for information from the patient
and/or a request for collection of at least one type of biomarker data
from the patient, and combinations thereof. For performance time 238, the
schedule of events 222 can specify timing of each event 237, such as for
a biomarker sampling at a particular time on three consecutive work days,
or one sample at time of wake-up, one sample thirty minutes later, and
another sample one hour later.

[0106] The guidance 230 for each event 237 and for any criteria 224, 226,
228 may include, for example, providing electronic reminders (acoustic,
visual) to start, end and/or wake up at a particular time, to perform a
bG collection at a particular time, to ingest a particular meal or
food(s) at a particular time, to perform a certain exercise(s) at a
particular time, take medication at a particular time, and the like.
Guidance 230 may also include information, questions and requests to
record particular information about physiology, health, sense of
well-being, etc., at a particular time, suggestion to improve compliancy
with the collection procedure, encouragement, and positive/negative
feedback.

[0107] It is to be appreciated that the events 237 define all the steps
that are necessary to be preformed in advance of as well as after a
biomarker sampling according to a request 240, such that a reproducible
set of circumstances, i.e., context before and/or after the sampling, is
created in the biomarker data for the biomarker sampling. Examples of
such biomarker data, in the context of diabetes, include fasting blood
glucose values, pre-prandial glucose values, postprandial glucose values,
and the like. Examples of a set of circumstances can include data
associated with the biomarker value which identifies collected
information in the patient data about meals, exercises, therapeutic
administration, sleep, hydration, and the likes.

[0108] Each of the events 237 in the schedule of events 222 can be
time-based, event-based, or both. An event 237 can also be a start of a
meal, a wake-up time, start of exercise, a therapeutic administration
time, a relative offset used with a prior glucose value, or a time
indicating movement above or below a predetermined biomarker value
threshold. The events 237 can also include any required patient actions
necessary to be performed in advance of and during biomarker sampling
such that reproducible circumstances are created at the time of biomarker
sampling. This can includes one or more of meals, exercise, therapeutic
administration, sleep, hydration, and the like. Additionally, the events
237 in the schedule of events 222 can be adjusted (number, types, timing,
etc.), to accommodate work schedule, stressors, and the like of the
patient 12.

[0109] As mentioned above previously, the adherence criteria 224 is used
to assess qualitatively whether an event 237 performed according to the
schedule of events 222 provided data which is acceptable to addressing
the medical use case upon which the structured collection procedure 70 is
based. In particularly, the adherence criteria 224 can provide variables
and/or values used to validate data from a performed event 237. For
example, an adherence criterion 224 can be a check performed by the
processor 102 of the collection device 24 that a value collected in
response to an event 237 is within a desired range, or is above, below,
or at a desired value, wherein the value may be a time, a quantity, a
type, and the like. The same or different adherence criteria 224 may be
associated with each of the events 237 within the schedule of events 222
as well with the entry criterion(s) 226 in one embodiment, and as being
the exit criterion 228 in another embodiment, such as illustrated by FIG.
6D (i.e., "stop exercising when bG back in target range" which defines
both the adherence and exit criteria). In one embodiment, one or more
events 237 in the schedule of events 222 may be modified (e.g., added,
deleted, delayed, etc.) if a particular event or events fail to met the
adherence criterion 224 for the particular event or events. In one
embodiment, the failure of the adherence criterion(s) 224 can trigger an
adherence event 242. In one embodiment, upon occurrence of an adherence
event 242 due to the associated adherence criterion 224 for an event 237
not being met or satisfied, the processor 102 may require one or more
additional actions to be performed as a consequence. For example, the
processor 102 may prompt on the display 108 additional information to the
patient, and/or prompt a question to determine whether the patient 12 is
sick, stressed, or unable to perform the request e.g., eat the meal, or
exercise. If the patient answers "Yes", e.g., via the user interface 146,
then as part of the adherence event 242 the processor 102 can provide a
delay to the schedule of event (i.e. suspend). In one embodiment, the
delay can continue until the patient indicated that he or she is better
in response to another question prompter by the processor 102, such as
the next day or after a predefined amount of time as also part of the
adherence event. For example, the patient 12, as part of an event 237, is
prompted by the processor 102 to administer a drug, but the patient is
not at home, such as for example, where his/her insulin is located. The
patient 12 can select the delay via the user interface 146, wherein the
processor 102 re-prompts the patient as part of the adherence event 242
after a predetermined amount of time. This delay may also have an upper
limit in which if the schedule of events 222 is not re-started within a
certain amount of the time, the structure testing procedure 70 in such a
circumstance may just end. In another embodiment, another form of an
adherence event 242 is a violation event, which results when the person
executing a structure testing procedure 70 fails to make a recommended
change in response to a request. For example, the request or part of an
event 237 may be for the patient to adjust a drug dosage from 10 U to 12
U, wherein the patient answers in the negative to a question on the
displayed on the display 108 asking if the patient will or has complied
with such a change. In response to such a violation event, the processor
102 may also send a message and/or provide a delay as previously
discussed above concerning the adherence event.

[0110] In another example and in one embodiment, a bG measurement must be
collected before each meal in order for a structured collection procedure
70 to provide data that is useful in addressing the medical use case or
question for which it was designed, such as identified by the use case
parameter 220. If, in this example, the patient fails to take a bG
measurement for the lunch meal in response to a request 240 for such a
collection according to the schedule of the event 222, and hence the
adherence criteria 224 for that event 237 fails to be satisfied, the
processor 102 in response to the associated adherence event 242 can be
programmed according to instructions in the collection procedure 70 to
cancel all remaining events 237 in the schedule of events 222 for that
day, mark the morning bG measurement stored in the data file (such as
data file 145 (FIG. 4) as invalid, and reschedule for the schedule of
event 222 for the next day. Other examples of further actions in which
the processor 102 may take in response to an adherence event 242 may be
to dynamically change the structure testing procedure by switch to a
secondary schedule of event, which may be easier for the patient to
perform, provide additional events for measurements to make up the
missing data, change the exit criteria from a primary to a secondary exit
criterion providing modified criterion(s), change the adherence criteria
from a primary to a secondary adherence criterion, fill in the missing
data for the failing event with historical data or an estimate based on
the historical data, perform a particular calculation to see if the
structured collection procedure 70 can still be successfully performed,
send a message to a particular person, such as a clinician, of the
failing event, provide a certain indication in the associated data record
152 to either ignore or estimate the missing data point, and the likes.
In still another embodiments, the adherence criteria 224 can be
dynamically assessed, such as for example, based on one or more biomarker
values and/or input received from the user interface in response to one
or more questions, via an algorithm which determines whether the
collected data provides a value which is useful in addressing the medical
use case or case. In this example, if the calculated adherence value is
not useful, for example, does not fall into a desired range or meet a
certain pre-define value, then further processing as defined by the
resulting adherence event would then take place, such as any one or more
of the processes discussed above.

[0111] The exit criteria 228, as mentioned previously above, establishes
the requirements for exiting or completing the structured collection
procedure 70, so that the structured collection procedure 70 has adequate
contextual data to answer the medical question addressed by the
structured collection procedure 70. The exit criterion 228 can help
increase the efficiency of the structured collection procedure 70 by
minimizing the number of required samples needed to address the medical
use case. By "addressing", it is meant that sufficient patient data has
been collected in which the clinician 14 may render an assessment to the
medical use case. In other embodiments, the assessment may be indicated
by a given confidence interval. A confidence interval is a group of
discrete or continuous values that is statistically assigned to the
parameter. The confidence interval typically includes the true value of
the parameter at a predetermined portion of the time.

[0112] As with the entry criteria 226, the exit criteria 228 can comprise
one or more of context specific exit criterion 244, procedure specific
entry criterion 246, and combinations thereof. Examples of context
specific exit criterion 244 can include one or more variables to identify
mood, desired blood glucose events (i.e., blood glucose level), to
indicate stress, illness, contraindications, such as for example,
hyperglycemia, hypoglycemia, vomiting, a fever, and the likes. Examples
of procedure specific entry criterion 246 can include one or more
variables to identify a number of events meeting the adherence criteria,
biomarker values being in a desired pre-determined range and/or at a
desired pre-determined value, a desired disease state, desired disease
status, no change in the biomarker after a pre-determined period, or no
significant progress over a pre-determined period to a desired biomarker
value, and the like. It is to be appreciated that in one embodiment the
exit criterion 228 can establish the condition(s) needed to be met for
entry criterion 226 of a second structured collection procedure 70. For
example, upon having a suitable Insulin-to-Carbohydrate (I:C) determined
with a first collection procedure, such as for example, structure
collection procedure 70b (FIG. 6B), running a structured test for
determining the best time for administering a bolus in regards to a start
of a meal, such as for example, structured testing procedure 70c (FIG.
6C), which needs a current I:C ratio, can be conditioned such that the
processor 102 can implement automatically a schedule of events of the
second structured collection procedure 70c upon meeting the exit
criterion of the first structured collection procedure 70b at some
unknown time. In other embodiment, for example, the exit criterion 228 of
a first structured collection procedure 70 that is being run by the
processor 102 according to the schedule of events 222 and the entry
criterion 226 of the second structured collection procedure 70 both can
be based on the same one or more contraindications, such as mentioned
above. In such an embodiment, upon occurrence of a contraindication being
provided to and/or detected by the processor 102, such as via the user
interface 146 and/or the biosensor 140, respectively, which in this
example meets the exit criterion 228 of the first structured collection
procedure 70, the processor 102 would automatically start the schedule of
events of the second structured collection procedure 70 as the entry
criterion 226 of the second structured collection procedure 70 has also
been met. An example of such a second structured collection procedure 70
which can be started via exiting a first structured collection procedure
can be one which has a schedule of events 222 which requests a biomarker
samplings at a routine interval, e.g., every 30 minutes, every hour,
every day at a particular time, etc., until the contraindication(s)
clears (e.g., biomarker value(s) reaches a desire range or value, patient
12 indicates to processor 102 via user interface 146 no longer having a
contraindication(s), expiration of a predefined period, etc.). Such an
embodiment is useful if recording the context and values of the events
after the occurrence of the contraindication(s) is a desire and in which
the first collection procedure should be exited when a
contraindication(s) occurs.

[0113] The exit criteria 228 can be a single criterion or multiple
criteria that establish the conditions to exit the structured collection
procedure 70. The conditions are provided in one embodiment such to
ensure that adequate contextualized biomarker data has been obtained to
answer the medical question being addressed by the collection method. For
example, such that a predetermined number of valid samples have been
acquired, or that the variability in the samples is below a predetermined
threshold. Therefore, it is to be appreciated that the end date and/time
of the collection procedure 70 may be dynamic and be changed
automatically by the processor 102 if the predefined condition(s) of the
exit criterion(s) 228 is not satisfied Likewise, the conditions of the
exit criterion 228 may be dynamic and be changed automatically be the
processor 102 such for example if a particular adherence criterion 224 is
satisfied or not satisfied. For example, in one embodiment if adherence
criterion 224 for a particular collection event 237 is met, then the
processor 102 is instructed to use a first exit criterion and if not met,
then the processor 102 is instructed to use a second exit criterion that
is different from the first exit criterion. Accordingly, until the exit
criterion 228 is satisfied, the end date and/time of the structured
collection procedure 70 can be at some unknown time in the future. In
another embodiment, the exit criteria 228 can be assessed after patient
data has been collected, such as, on historical patient data.

[0114] It is to be appreciated that the entry and exit criteria 226, 228
together with the adherence criteria 224 can help to reduce both the time
to perform the structured collection procedure 70 and the expense
associated with the collection by defining one or more of the acceptable
conditions, values, structure and context needed to perform the schedule
of events 222 in an effort to make every collection event 237 count
and/or reduce consumption of test strips 30 with unneeded collections
that do not help address the medical use case or question. Hereafter
reference is made to FIGS. 6A-6E.

[0115] Structured Collection Procedure Examples

[0116] FIGS. 6A-E illustrate examples of some structured collection
procedures 70a, 70b, 70c, and 70d depicting their functions which can
easily be translated by one of ordinary skill in the related art into
instruction code which may be implemented on any one of the devices the
above described devices 18, 24, 25, 26, 28, 36, 52. Therefore, for
brevity, no discussion is provided in regard to pseudo-code or actual
code relating to these illustrated functions.

[0117] FIG. 6A diagrammatically illustrates an embodiment of a structured
collection procedure 70a used to obtain contextualized biomarker data
from a diabetic patient. The horizontal axis shows the performance times
238 of the various events 237, and the vertical axis shows adherence
criterion 224 without values. In the illustrated embodiment, the events
237 can include recording information regarding a meal 248 and sleep 250
in which to provide context 252 for the five-biomarker samplings 254 also
events 237 that are part of the schedule of events 222. In this example,
the adherence criterion 224 for the meal 248 can be a value which must be
greater than a minimum value, e.g., for a carbohydrate amount. The entry
criterion 226, for example, can comprise a biomarker value being above a
particular value such as required to meet contextualization requirements
to begin the structured collection procedure 70a. The exit criterion 228
as well can comprise a biomarker values being below a particular value
such as also required to meet contextualization requirements to end the
structured collection procedure 70a. Such a structured collection
procedure 70 is useful for helping to address a number of medical use
cases.

[0118] GLP1 Structured Testing Procedure

[0119] For example, several epidemiological studies have confirmed that
elevated postprandial glucose (PPG) levels are a significant predictor of
cardiovascular mortality and morbidity in type 2 diabetes (T2D). For this
reason, there is a family of human once-weekly long acting glucagon-like
peptide-1 (GLP 1) drugs which can be prescribed to T2Ds who show high
post prandial bG values. These GLP 1 drugs are similar to the natural
hormone GLP-1 which has a key role in blood sugar regulation by
stimulating insulin secretion and suppressing glucagon secretion.
Therefore, a structured collection procedure 70 can be provided in one
embodiment which proposes an intensive measurement of bG values during
the time after one or more meals over time allows therapy efficacy to be
shown by means of observed reduced postprandial bG values. Based on such
observed values, doses recommendation for a GLP 1 drug and/or whether a
particular GLP 1 drug is the right drug at all for the patient can be
determined.

[0120] For example, the structured collection procedure 70 could be
provided on a collection device 24 for when a patient has been prescribed
to administer a particular drug, e.g., a GLP 1 drug. In the case of a GLP
1 drug, in which determination of drug efficacy is desired, the entry
criterion 226 for such a structured collection procedure could then be
that the patient must affirm to the processor 102 in response to a
question displayed on the display 108 to perform the structured
collection procedure 70 over a period of time (e.g., over the next 4 to
24 weeks) and/or the processor 102 has determined that the mean PPG level
of the patient from prior post prandial bG values over a period (e.g.,
week, month, etc.) are high (e.g., greater than 141 mg/dl). Still other
factors could be used as the entry criterion(s) 226, such as fasting
blood glucose being more than a certain value, e.g., 126 mg/dl or less
than a certain value, e.g., 240 mg/dl.

[0121] After the conditions of the entry criterion(s) 226 have been
satisfied and confirmed by the processor 102, the schedule of events 222
is then automatically run by the processor 102. The schedule of events
222 would specify desired collection events 237 in which the processor
102 would automatically prompt the patient for entering post prandial bG
values after breakfast, lunch, and dinner (i.e., performing a bG
measurement on a sample provided to a test strip that is read by the
measurement engine and provided to the processor for storing in a data
record and display). As customized by the prescribing physician, the
schedule of events 222 could also define a collection event 237 with a
performance time 238 in which the patient must administer the drug as
well as to provide a reminder of the dosage and a request 240 for
confirmation from the patient when the drug has been administered. For
example, the processor 102 in executing the schedule of events 222 would
automatically prompt the patient to administer dosages at the times
specified by the collection events 237 in the schedule of events 222,
e.g., 10 mg of Taspoglutide on a certain day of the week, and then after
a period, a second dosage according to a second interval, e.g., after 4
weeks, then 20 mg also on a certain day of the week. A collection event
237 could also be defined in the schedule of events 222 in which the
processor 102 makes a request on the display 108 for information, such as
whether the patient is feeling well, to provide an indication of energy
level, to provide an indication of size of meals consumed, and the like.

[0122] A condition(s) for the adherence of each entered post prandial bG
value could be provided via the use of adherence criteria 224 in which
any post prandial bG value entered (i.e., measured) an amount of time
before or after the prompting, e.g., a testing window of ±30 minutes,
such a measured value would not be accepted as a valid measurement for
the schedule of events 222 by the processor 102. In one embodiment, the
processor 102 can take further action automatically based on the
adherence criteria 224 assessment preformed automatically by the
processor 102. For example, if a bG measurement was taken before a
measurement prescribed by a collection event in the schedule of events
222 and outside the defined testing window, e.g., -30 minutes before the
collection event time, the processor 102 in such a case will
automatically notify the patient that a measurement is still needed at
the prescribed time as the previous measurement was not accepted since
outside the testing window. Likewise, if after the testing window, e.g.,
the collection event time +30 minute, the processor 102 can automatically
notify the patient that the previous measurement was not accepted since
outside the testing window and provide encouragement on the display 108
to the patient to make an effort take a measurement within the testing
window.

[0123] The exit criterion 228 for such a GLP 1 structured collection
procedure 70 could be an indication that the mean bG value, in using a
minimum amount of time (e.g., days, weeks, months, etc.), a minimum
number of accepted measurements, or both, has reached a desire value.
Likewise, the exit criterion 228 could be an indication that the mean bG
value, after a maximum amount of time (e.g., days, weeks, months, etc.),
a maximum number of accepted measurements, or both, has not reached a
desire value. Still further, the exit criteria 228 can be other factors
which indicate that the drug or dosage is not at all right for the
patient, such as the patient responding as having nausea and/or vomiting
each day for a minimum number of days in response to a collection event
for such information prompted by the processor 102 on the display 108.
Still other factors could be used as the exit criteria 228, such as
fasting blood glucose being less than a certain value, e.g., 126 mg/dl or
greater than a certain value, e.g., 240 mg/dl. The data collected from
such a drug base structured collection procedure 70 can then be used by a
physician to make a dosage recommendation for the GLP 1 drug and/or
determine whether the particular GLP 1 drug is the right drug or not for
the patient.

[0124] Another example is diagrammatically depicted by FIG. 6B which shows
a structured collection procedure 70b which has a defined medical use
case parameter 220 indicating that the procedure can be helpful for
determining suitability of an insulin to carbohydrate (I:C) ratio. As
illustrated, the entry criterion 226 is defined as having the patient
simply acknowledge guidance 230 of selecting a fast-acting meal, to note
that the insulin dose is calculated with the current I:C ratio as well as
agreeing not to exercise, take additional food or insulin during the
testing period. For example, the processor 102 can present on the display
108 such guidance 230, which the user can then acknowledge after reading
with either a "Yes" or a "No" entered via using the user interface 146
for the desired entry choice. If the user enters "Yes", then the entry
criterion 226 is satisfied, and the processor 102 automatically starts
the schedule of events 222 defined in the structured collection procedure
70b. In another embodiment, the entry criterion 226 may be or include
satisfying a request for selecting a fast-acting meal. For example, the
request 240 for selection can be the processor 102 displaying on the
display 108 a selection menu providing a listing of fast-acting meals to
which input of such a selection via the user interface 146 is needed. For
example, selection of a fast-acting meal may be made via a press of one
of the buttons 147, 149 or via the touch screen interface if provided by
display 108. Such a selection can then be stored in memory 110 of the
collection device 24 such as setup data 163 (FIG. 4) which may be part of
the data file 145 (FIG. 4) for the structured collection procedure 70b.
In an alternative embodiment, a particular fast-acting meal may be
recommended by the structured collection procedure 70b.

[0125] As shown, the schedule of events 222 can comprise one or more
events, such as the plurality of events 237a-k illustrated and with each
having associated performance times 238a-k and requests for action
240a-k. As shown, the requests for action 240a-c, and 240f-k are requests
for the user to take a bG level measurement, request 240d is to take an
insulin dose, and request 240e is to eat the fast acting meal. Also shown
is that events 238f-k each have an adherence criterion 224, which must be
met if the data for events 238f-k are to be recorded in the data file
145. In this example, the adherence criteria 224 requires that the
actions 240f-k be completed within .A-inverted.20 minutes of their
corresponding performance times 238f-k in order for a data record 152
recording the received value(s) for the corresponding event 237f-k to
count towards completing the collection procedure 70b. In one embodiment,
the processor 102 will make each of the requests 240a-k at their
associated performance times 238a-k in order to obtain resulting data
values e.g., data values 256a-k (FIG. 4) at the time the requests are
performed.

[0126] For example, the processor 102 can prompt the patient 12 with a
request 240a to take a bG level (biomarker) measurement at performance
time 238a. The resulting measurement when received by the processor 102,
such as automatically from the measurement engine 138 after reading the
test strip (biosensor) 140 for the desired biomarker, is then recorded
automatically by the processor 102 in the date file 145 as a
corresponding data value 256a for the associated event 237a. For actions
240d and 240e, at a required time, the processor 102 can automatically
prompt the patient 12 to take the prescribed action at the required time,
and again automatically prompt the patient thereafter to confirm that the
required action has been taken, or that a predefine status has been
achieved. A date-time stamp 169 can also be provided in the date record
152 automatically by the processor 102 upon triggering of the requests
240a-k, acknowledgement of the requests 240a-k, upon completion of the
event 237a-k, upon receiving a data value 256a-k for the event 237a-k,
and combinations thereof. Additionally, in another embodiment, the
patient 12 can record data values 256a-k for one or more events 237a-k by
entering the data directly into the device 24 via the user interface 146,
wherein the processor 102 stored the entered data values/information in
the associated data record 152 for the event 237a-k, or in other
embodiments can record a voice message with the information for later
transcription into digital data. In still other embodiments, the patient
12 can be guided by the collection device 24 to record data for an event
237a-k using a paper tool 38.

[0127] As mentioned previously above, each event 237 can be a recording of
a biomarker value, or a request for a required patient action that is
necessary in order to create a context for the biomarker value, such as
for example, meals, exercise, therapeutic administration, and the like.
In the illustrated embodiment, the context 252 for completing events
237a-c is to establish a pre-prandial baseline and a no-trend condition,
and for events 237f-k to establish a post-prandial excursion and tail.
Such context 252 for these events may also be associated with the
corresponding data records 152 for each event as contextual information
156 (FIG. 4). Such information is useful later when reconstructing the
data and/or when there is a desire to know the context for which the data
record was created.

[0128] It is to be appreciated that any patient action taken outside of
the required requests for patient actions 240a-k can also be recorded by
the processor 102 but will not be considered by the processor 102 as part
of the collection procedure 70b. Data 256a-k for events 237a-k that are
prospective can be identified based on a type of event, the time of the
event, the trigger of the event, and combination thereof. Each of the
performance times 238a-k can be fixed or variable based on prior data.
Some of the event 237a-k in other embodiments can also be a past,
current, or a future event such as for meals, exercise, and the like, or
data values such as for hypoglycemic events, hyperglycemic events, or
data of a specific value of interest. In some embodiments, the events
237a-k can be identified via a paper tool 38 that is procedure based.

[0129] As also shown, the structured collection procedure 70b will end if
the condition of the exit criterion 228 is satisfied. In this example,
the exit criterion 228 is satisfied if at least three of the actions
240f-k met the adherence criterion 224. For example, the processor 102
may provide a unique identifier (e.g. an incremental count) 167 (FIG. 4)
in the data file 145 for each event 237a-k performed and to which
satisfied the adherence criterion 224 if required. In the illustrated
embodiment of FIG. 4, events 237a-c and 237e-k each receive a unique
identifier but not event 237d, e.g., <null>, since not satisfying
an associated adherence criteria (not shown). In addition, analysis logic
258 and resulting recommendations 260 can also be provided in the
structured collection procedure 70b which the processor 102 may apply
automatically to the data collected upon satisfying the exit criterion
228 in one embodiment.

[0130] Similar features are also provided in the examples illustrated by
FIGS. 6C and 6D, wherein FIG. 6C depicts a structured collection
procedure 70c which has a defined medical use case parameter 220
indicating that the procedure is helpful for determining suitability of a
bolus in regards to a meal start. Likewise, FIG. 6D depicts a structured
collection procedure 70d which has a defined medical use case parameter
220 indicating that the procedure is helpful for determining suitability
of an exercise equivalent to a carbohydrate intake. In addition to the
above examples, other such structured collection procedures may be
designed to address other various medical use cases such as, for example,
the following: determining the effects of eating a particular food on a
biomarker level of a patient; determining the best time to take
medication before and/or after a meal; and determining the affect of a
particular drug on a biomarker level of a patient. Still other structured
collection procedures can be provided which may be useful in addressing
questions concerning how best to initialize therapy for a patient,
finding a determination of status of a patient disease progression,
finding the best ways to optimize a patient therapy, and the like. For
example, the clinician 14 can define and/or use a pre-defined structured
collection procedure 70 which looks at factors which may have an effect
on the therapy of the patient. Such factors can include, for example,
stress, menstrual cycle, pre-dawn effect, background insulin, exercise,
bolus timing with respect to a meal, basal rate, insulin sensitivity,
post-prandial behavior, and the like.

[0131] FIG. 6E shows a diagram structured collection procedure 70
comprising one or more multiple sampling groups 262 each comprising a
recurring schedule of events 222 provided between the entry criterion 226
and the exit criterion 228. In this example, the schedule of events 222
comprises one or more events 237 occurring each day at consistent times
of day. As the structured collection procedure 70 in the process of
obtaining contextualized biomarker data from a diabetic patient 12 can
span over multiple days, even week and/or months before the exit
criterion 228 is met, one or more checks 264, such as for parameter
adjustment, and/or evaluation of whether to re-run the sampling groups
262, can also be provided between the entry and exit criterions 226, 228
in one embodiment. The duration between such checks 264 can be used for
physiological system equilibration, evaluation of treatment efficacy, or
convenience. For example, either between each sample grouping 262 or
after a predefined number such sampling grouping 262 (as shown), an
analysis for the check 264 can be performed by the processor 102 to
determine whether an adjustment to any parameter in the collection
procedure 70 is needed.

[0132] For example, such analysis may be either for a parameter
optimization or efficacy assessment. For the parameter optimization, the
processor 102 can run calculations on the samples provided within a
previous schedule of events 222 or sample grouping 262, using information
from prior optimizations, clinician set parameters, and a collection or
therapy strategy, recommends a new parameter value. For the efficacy
assessment, the processor 102 can evaluate data not utilized by the
optimization analysis. Additionally, it is to be appreciated that after a
group of samples, i.e., sampling group 262, are taken the processor 102
can also evaluate the data from the sampling group 262, such as if such
data is need in order to alter/optimize a person's therapy. Adherence
criteria can be applied to perform this evaluation to the data of the
sampling group 262 or set. For example, a first adherence criterion 224
can be used by the processor 102 to assess whether a minimum amount of
data is provided by the sampling group 262 and if not, for example, the
alteration/optimization of the patient's therapy will not take place.
Another adherence criterion 224 could permit the processor 102 assess
whether the data is acceptable to permit an adjustment called for by the
check 264, such as looking at spread of the data, whether these is too
much variability (noise), as well as other data attributes to use the
data. In this example, if meeting such adherence criterion, then
processor 102 has assessed that there is minimum risk that adjusting a
parameter of the procedure could readily result in a severe event, e.g.,
hyper- or hypoglycemic event. Lastly, an adherence criterion can be used
by the processor to assess the exit criteria based on the data of
sampling group, for example, the exit criterion is met when the data from
the sampling group 262 satisfies the adherence criterion, such as for
example, discussed above, for the sampling group.

[0133] It is to be appreciated that collection or therapy strategies can
be categorized into scale based (sliding or fixed) assessments or formula
based assessments. As input to the collection or therapy strategy, the
processor 102 in one embodiment can utilize the data collected from a
predetermined number of prior sample grouping(s) 262. This data can be
either used as individual points (only the formula based collection or
therapy strategies), or combined with filtering for use in a scale based
assessment. In another embodiment, for example, the result of a check 264
performed by the processor 102 can also result in a status or
recommendation being provided by the processor 102 automatically. Such
status or recommendation may be e.g., a status of continuing with current
parameter values, a recommendation to change particular parameters, a
recommendation to change the adherence and/or exit criterion, a status
that the processor 102 switched to a secondary adherence and/or exit
criterion based on the analysis performed on the data from a prior
schedule of events or prior sample grouping, or a recommendation to
terminate the collection procedure, and the likes. A discussion of
performing a structured collection using a structured collection
procedure according to an embodiment of the present invention is provided
hereafter with reference made to FIG. 7A.

[0134] Structured Collection

[0135]FIG. 7A depicts a structured collection 300 for diagnostic or
therapy support of a patient with a chronic disease. The method 300 may
be implemented as instruction codes of a program running on a computer
with a processor and memory, such as preferably clinician computers 25
(FIG. 2) as stand-alone software, as part of software 34, or as software
provided as a service by server 52 via a secure web implementation over
public network 50. Upon a processor 76 executing the program from memory
78 of the clinician computer 25, as one function among others, the
processor 76 after receiving a query for a medical use case and/or
question, searches memory 78, computer readable medium 40, and/or server
52 for all structured collection procedures 70a-d, which matches the
submitted query in step 302. For example, the processor 76 may read the
medical use case parameter 220 of each available structured collection
procedures 70a-d and using a conventional search algorithm (e.g., list,
tree, heuristics, etc.), provide on a display 82 a selection choice for
those structured collection procedure matching the query in step 304 in
one embodiment.

[0136] In one embodiment, the list displayed can reflect, for example, the
structured collection procedures 70a, 70b, 70c, and 70d available for use
from the server 52. In still another embodiment, the list of selection
choices displayed can be dynamically created based on a type of medical
use case the clinician 14 wishes to investigate. For example, prior to
step 302, a list of selectable medical use cases can be displayed on the
display 82 by the processor 76. In such an embodiment, the clinician 14,
using the user interface device(s) 86 may selected from among the
displayed medical use cases, for example, the medical use case
"Determining meal effect on patient's therapy." After the clinician makes
such a selection, which the processor 76 receives as input from the user
interface device(s) 86, the processor 76 after using decision logic
(e.g., if . . . then) provided by the software 34 would then display in
step 304, for example, structured collection procedure 70b (e.g., a
structured collection procedure to determine a more accurate
insulin-to-carbohydrate ratio) and 70c (e.g., a structured collection
procedure to determine bolus timing in regards to meal start), and not
structured collection procedures 70a and 70d, which are structured
collection procedures unrelated to the medical use case. Likewise, a
"show all structured collection procedures" could also be a choice among
the displayed medical use cases, in which the complete list of available
structured collection procedures would then be displayed in step 304. In
another embodiment, step 302 may be skipped and the processor 76 in step
304 can just provide a display of the structured collection procedures
70a-d available in memory 78 of the clinician computer 25.

[0137] In step 306, a clinician using the user interface devices 86 can
select a structured collection procedure 70 on the computer 25 for
diagnostic or therapy support. For example, the selecting process can
include choosing from the list displayed in step 304, which provided one
or more structured collection procedures. After the clinician makes such
a selection in step 306, which the processor 76 receives as input from
the user interface device(s) 62, the processor 76 of the computer 25
retrieves automatically from an electronic component, e.g., computer
memory 78, server 52, or computer readable medium 40, and displays the
selected structured collection procedure 70 on display 82 for viewing.

[0138] It is to be appreciated that each structured collection procedures
70a, 70b, 70c, and 70d is based on a medical use case and has parameters
defining entry criteria 226, a schedule of events 222, adherence criteria
224, and exit criteria 228. As mentioned above, the entry criteria 226
establish the conditions needed to be met prior to obtaining biomarker
data from the patient. Each event 237 of the schedule of events 222
comprises a performance time, patient guidance to perform the event,
patient actions, a request for information from the patient, a request
for collection of at least one type of biomarker data from the patient,
and combinations thereof. The adherence criteria 224 is used to
qualitatively assess whether an event 237 performed according to the
schedule of events 222 provided data which is acceptable to addressing
the medical use case upon which the structured collection procedure 70 is
based. Additionally, as mentioned above, the exit criteria 228 establish
the conditions needed to be met prior to exiting the structured
collection procedure 70.

[0139] In step 310, after the processor 76 displays the selected
structured collection procedure 70, the clinician 14, to meet the needs
of the patient 12 and/or interests of the clinician, may adjust any one
of the parameters 222, 224, 226, and 228 which are also displayed on the
display 82. Safe guards may be implemented to ensure that only the
clinician 14 can modify such parameters and/or run the software 34, such
as via password protection. The processor 76 receives any such changes to
the parameters 222, 224, 226, and 228 as input via user interface devices
86 and saves the revised structured collection procedure 70 in memory 78.
Next, in step 312, the selected structured collection procedure 70 is
prescribed on the computer 25 to the patient 12 by the clinician 14,
wherein the processor 76 of the computer 25 provides as output the
selected structured collection procedure 70 to the patient 12 to perform.
For example, in step 314, the prescribed structured collection procedure
70 is implemented electronically on a processor based device, such as
collection device 24, or any of the other above described devices 18, 28,
and 36 (FIG. 1), as part of the software 34 or in other embodiment,
portions thereof as part of paper tool 38.

[0140] In one embodiment, the prescribed structured collection procedure
70 may be implemented from the clinician computer 25 (FIG. 2) to the
collection device 24 via communication link 72, via the public network 50
through a webpage and/or made available for downloading on server 52. In
still other embodiments, the prescribed structured collection procedure
70 can be provided through the computer readable medium 40 and loaded by
one of the devices 18, 24, 28, and 36, downloaded from another one of the
devices 18, 24, 25, 26, 28, and 36, or downloaded via cell phone or
telephone connection from server 52. Notice that a new/updated/prescribed
structured collection procedure 70 available for use on the devices 18,
24, 25, 26, 28 and 36 may be provided in any standard fashion, such for
via postal letters/cards, email, text messaging, tweets, and the likes.

[0141] Customizing a Structured Collection Procedure

[0142] FIG. 7B conceptually illustrates one example of a pre-defined
structured collection procedure 70, which has a defined medical use case
parameter 220 indicating that the procedure is helpful for medical use
cases or questions which need to know the trends in blood glucose (bG)
levels of a patient and/or the relationships between blood glucose values
and time of day, meal size, and energy level. As mentioned above
previously, the use case parameter 220 can be used as an identity tag in
which the processor 102 may locate the associated structured collection
procedure 70 in response to a search query, such as, for entered use case
or question. For example, the search query can be entered into the
collection device 24 via the user interface 146 and/or received from the
clinician computer 25. Such a search query may result from a desire to
know which uses case can be addressed by the structured collection
procedures 70 currently available on the collection device 24, or to know
which structured collection procedure 70 would be useful to address a
particular use case or question. Therefore, the use case parameter 220 in
one embodiment permits a structured collection procedure 70 to be
automatically chosen by the processor 102 from a plurality of structured
collection procedures 70a-d, such as provided in memory 110, memory 78,
computer readable medium 40, and/or server 52 based on a selection, such
as from a displayed list on the display 108 provided by the processor
102, or from input received by the processor 102 from the user interface
of a defined medical question. In other embodiments, the use case
parameter 220 may also indicate the structured collection procedure 70 is
also useful for showing relationships between bG level values and time of
day, meal size, and/or energy level.

[0143] In one embodiment, the pre-defined parameters of the structured
collection procedure 70 can be displayed for modification/customization
by the processor 102 of the collection device 24 on the display 108
and/or by the processor 76 of the clinician computer 25 on the display 82
by an authorized user. Such an authorized user may be identified, for
example, on the collection device 24 and/or the clinician computer 25 by
a password entered via the user interface 146, 86, respectively. In such
an embodiment, the pre-define parameters of structured collection
procedure 70 can be displayed on the display 108, 82 in which
customizable parameters can provide editable or selectable variables via
drop-down boxes with various selection choices, radio buttons, check
boxes, formatted fields requesting a specific type of information
(mm-dd-yyyy, number, letter, etc.), text boxes to enter messages to be
displayed, and the likes. The structured collection procedure 70 can be
displayed for editing in tabular format (as illustrated) in one
embodiment or in a sequential manner listing one parameter at a time in a
scroll-through fashion in another embodiment. In still another
embodiment, structured collection procedures can be provided which cannot
be modified.

[0144] As shown by FIG. 7B, the structured collection procedure 70 may
further comprise parameters defining one or more criterions setting the
conditions needing to be met by the patient 12 to start of the structured
collection procedure, i.e., entry criterion(s) 226, to end the structured
collection procedure i.e., exit criterion(s) 228, and combinations
thereof. In one embodiment, the processor 102 of the collection device 24
uses the one or more criterions to automatically start, evaluate, and end
the structured collection procedure 70 if the condition(s) defined by the
structured collection procedure are met. In still another embodiment,
adherence criterion(s) 224, which are the conditions needing to be met in
order for the collected datum/data to be accepted, can also be provided
in the structured collection procedure 70.

[0145] As also shown in FIG. 7B, the structured collection procedure 70
further comprise parameters defining one or more (collection) events 237
which together form the schedule of events 222. Each of the events 237
comprises one or more requests 240, e.g., for a measurement from the
measurement engine 138 of a biomarker value for a sample provided to the
biosensor 140, and/or for information to be entered by the patient via
the user interface 146 such as in response to a question presented by the
processor 102 on the display 108. In the illustrated embodiment, the
requests 240 are for a bG measurement, a meal size indication (S, M, or
L), and an energy level indication (1, 2, 3, 4, 5), in which 1 is lowest
and 5 is highest. Other such requests 240 can include indicating whether
the patient exercised, indicating a particular food that was consumed,
indicating which medicine was administered, indicating dosage of the
medicine administered, and the like may also be provided in other
structured collection procedures 70. In the illustrated embodiment, the
collection events can be customized by selecting which request 240 the
processor 102 should perform via a yes/no selection box.

[0146] The structured collection procedure 70 may also include guidance
230 and timing or performance time 238 associated with each of the
collection events 237 as well as with each of the entry, exit, and
adherence criterion/criteria 226, 228, and 224. Such guidance 230 is
provided by the processor 102 to the display 108 upon the occurrence of
the associated collection event 237 or other parameters. For example, a
collection event 237 for a bG measurement before breakfast may also have
a request 240 for an indication of the energy level of the patient.
Therefore, in this example, the associated guidance 230 which states,
"Please indicate energy level" is provided on the display 108 by the
processor 102. It is to be appreciated that the guidance 230 is a text
box, field, area, which enables for information to be provided to the
patient to help the patient in performance of the structured collection
procedure 70. In this example, selection of a number from 1 to 5 may be
made via press of one of the buttons 147, 149 or via the touch screen
interface if provided by display 108 as a data entry for such a request
237, which is then stored by the processor 102 in memory 110 of the
collection device 24 as part of a data file 145 (FIG. 4) for the
structured collection procedure 70.

[0147] The timing parameter 238 of the structured collection procedure 70
is used to specify for any one of the associated collection event 237,
the entry, exit, and adherence criterion/criteria 226, 228, 224, either a
specific date and/or time (mm-dd-yyyy, hh:mm), or a period (n) after a
preceding collection event in which to perform the associated collection
event. The periods n1, n2, n3 in the illustrated
embodiment for the respective collection events 237 indicate hours, but
in other embodiments can be indicated in minutes or seconds. In another
embodiment, the timing or performance time parameter 238 for an
associated collection event 237 and for the entry, exit, and adherence
criterion/criteria 226, 228, 224 can be modified by another collection
event and/or by the criterion/criteria.

[0148] For example, in the illustrative embodiment, the entry criterion
226 is modified by the adherence criterion 224 by adding a day if the
guidance 230 provided in the form of a question "Are you willing to
conduct a test over 3 consecutive days?" is not affirmed by the patient
12 e.g., via a "No" selection provided on the collection device 24. In
this illustrated example, the "Affirms guidance" may be a drop down
selection provided in a combo box for customizing the adherence criterion
224 of the associated collection event 237, which when selected causes
the processor 102 to wait for the accepted/not accepted input (e.g., via
buttons 147, 149) before executing the remaining logic ("if not add 1 day
to timing") of the adherence criterion 224. Still further in this
example, the processor 102 in accordance with the logic provided in the
adherence criterion 224 associated with the exit criterion 228, can set
the timing or performance time parameter 238 of the exit criterion 228 to
the date (mm-dd-yyyy) that is 3 days after completing the entry criterion
226. It is to be appreciated that the various possible combinations of
logic statements which may be performed by the structured collection
procedure 70 can be pre-defined and selected by a drop down box in order
to be customized in one embodiment, and/or logic statements can be built
in another embodiment.

[0149] The structured collection procedure 70 can also includes an options
parameter 232 associated with each of the collection events 237 as well
as with each of the entry, exit, and adherence criterion/criteria 226,
228, 224. The options parameter 232 can have a customizable value(s) to
govern whether the data and/or results of the associated collection event
237 or any of the other parameters e.g., entry, exit, and adherence
criterion/criteria 226, 228, 224, in the structured collection procedure
70 meets a particular condition such that still further processing may be
carried out by the processor 102 if such a condition(s) is meet. For
example, such options can be to have the processor 102 automatically send
a message to the physician indicating that the patient has started the
structured collection procedure 70 via satisfying the entry criterion
226, or to provide a message to the patient and/or the physician if the
patient fails a collection event 237 by not satisfying an adherence
criterion, or to provide a message to the physician when the patient
completes the structured collection procedure 70 when the exit criterion
is satisfied, or combinations thereof. For example, such an options
parameter 232 can have a global list of such actions which is selected on
the display 108, for example, by a selected value from a range of values
associated with each option. For example, the options for each parameter
can be customized via selecting from a drop down box having option
choices (e.g., 1, 2, 3, 4, 5, . . . , A, B, C, etc.) and in which, for
example, Option 1 of having the processor 102 provide a message to the
physician if the patient fails a collection event 237 (e.g., by not
satisfying an adherence criterion), is shown selected for the before
breakfast collection event 237. An example in the context of patient 12
being diabetic is provided hereafter to illustrate further such features
provided on a collection device 24 according to the present invention.

[0150] A typical patient with Type 2 diabetes may measure his/her blood
glucose once per day after waking up in the morning. At a routine office
visit, the patient's HbA1C result is found to be elevated. The physician
recommends that the person goes through three days of intensified glucose
monitoring, and selects the structured collection procedure which is
useful for this purpose. The structured collection procedure 70 is then
customized as discussed above such that during these three days
collection events 237 are defined with a number bG measurement requests
240 such that the patient can be requested by the processor 102 to
measure his/her blood glucose before and two hours (e.g., n1=2)
after breakfast, before and two hours (n2=2) after lunch, before and
two hours (n3=2) after supper, and at bedtime. Additionally, the
patient 12 can be requested via other associated requests 240 for each
collection event 237 to provide an assessment of the relative size of the
ingested meals at the appropriate times as well as an indication how
he/she feels with regard to energy level. In the illustrate embodiment of
FIG. 7B, the processor 102 can request the indication of energy level
with each collection event 237 and the assessment of the relative size of
the ingested meals every other collection event 237 (i.e., after the
meal). Furthermore, the physician has provided a condition via adherence
criterion 224 of having to perform the meal assessment within ±30
minutes of period (n) of the associated collection event 237 in order for
such information to be useful in the assessment. Such information is
useful to contextualize the collected data and for the analysis performed
on the collected data.

[0151] Additionally, the physician would like to be notified when the
patient has failed to complete the "before breakfast" collection event
237. Therefore, to facilitate the notification option, the physician
customizes the structured collection procedure 70 by set the options
parameter 232 associated with the "before breakfast" collection event,
via a drop down box to "Send a message to the physician if adherence
criterion fails." All other collection events 237 have their associated
options parameter 232 default to indicate that the processor 102 is not
to take any additional action with regards to the options parameter. It
is to be appreciated that the above described features and arrangements
in the illustrated embodiment of FIG. 7B, provide a simple and convenient
interface and method for customizing a structured collection procedure,
such as for parameter adjustments carried out in step 310 of method 300
previously discussed above in reference to FIG. 7A.

[0152] Implementing and Performing a Structured Collection Procedure

[0153] FIG. 8A shows a flowchart of the method for implementing and
performing a structured collection procedure 70 to obtain contextualized
biomarker data from a patient 12 according to an embodiment of the
invention. It is to be appreciated that a number of structured collection
procedures 70a-d (FIG. 2) prescribed in step 312 and implement in step
314 (FIG. 7A) may be stored in memory 110 (FIG. 3) of the device 24 and
selected for execution at any desired time. For example, upon pressing a
certain combination of the buttons 147, 149, the patient can select a
desired structured collection procedures 70a-c and the date when to start
a structured testing collection i.e., a set mode function. For example, a
date range to choose from may be to begin the testing tomorrow and end at
today +90 days, which the processor 102 can also recorded in the data
file 145 (FIG. 4) as part of the setup data 163. In such an
implementation, the processor 102 as instructed by the software 34 reads
the setup data 163 for the selected structured collection procedure 70
and indicates on the display 108 that the device 24 is in a structured
testing mode, for example, from one day before the chosen focused testing
start date until the end of the structured collection procedure.

[0154] It should be appreciated that multiple structured collection
procedures 70a-d can be executed sequentially or simultaneously at any
given time. However, in one embodiment, the software 34 permits the user
only to schedule another structured collection procedure 70 if the start
date is later than the end date of the current structure collection
procedure 70 being executed. The software 34 also permits the user to
override a scheduled date for a structured collection procedure 70. If a
structured collection procedure 70 is scheduled and the user enters the
set mode function again, the software 34 causes the processor 102 to
display the scheduled date on the display 108 as the default date; if the
user exits the set mode without modifying the date, the previously
scheduled date stays active. If a structured collection procedure 70 has
started, the software 34 permits the user to enter the set mode and cause
the processor 102 to cancel the current structured collection procedure
70. Upon cancellation, in one embodiment, the software 34 causes the
processor 102 to de-tag (e.g., null the unique identifiers 167) the data
records 152 in the data file 145 for the data collected for the cancelled
structured collection procedure 70.

[0155] Upon reaching the procedure start in step 316 (FIG. 8a), the
processor 102 evaluates the whether entry criterion(s) 226 is met in step
318 to begin the structured collection procedure 70 selected to obtain
biomarker data to address a predefined use case or question (e.g., use
case parameter 220). In step 320, the processor 102 specifies requests
240 according to their associated timing 238 for each event 237 in the
schedule of events 222 for the structured collection procedure 70. It is
to be appreciated that the schedule of events 222 provides a sampling
plan for biomarker data collection that is performed by the processor 102
to obtain biomarker data in a predefined context. In performing the
schedule of events 222 in step 320, the software 34 causes the processor
102 to assign a unique identifier (e.g. incremental count) 167 in a date
record 152 which corresponds to each event 237 in the structured
collection procedure 70. Optionally, each criterion 226, 228, 224 may
also be provide with a date time stamp 169 to indicate when such
criterion was satisfied, if desired.

[0156] Adherence criterion 224 is then applied to the input received
(e.g., biomarker data or information) in response to a request 240 to
determine whether the input received meets the adherence criterion 224.
When a structure collection procedure 70 has started, all data collected
according to requests 240 in the structured collection procedure 70 and
which satisfy the adherence criterion 224, if required in step 322, are
then assigned (tagged) in the data file 145 by the processor 102 with the
unique identifier 167 in step 324. It is to be appreciated that the
unique identified also serves to associates the collected data e.g., data
values 256 with their event 237, the request 240, and a date-time stamp
169 to indicate when the collection in response to the request 240 was
received by the processor 102. While a structured collection procedure 70
is being executed, in one embodiment the software 34 permits the user to
perform a measurement on the device 24 at any time without interfering
with the episode.

[0157] In one embodiment, the software 34 permits reminders for biomarker
measurements to be `snoozed` as mentioned above for a period, such as for
example, 15 minutes and up to a number of times, for non-critical
measurements. In another embodiment, biomarker measurements or data
entries that are performed close enough in time to a request 240 in step
320 are designed as valid measurements or data entry for the request 240
by the software 34. As such, the processor 102 will tag the associated
data record 152 for the event 237 with the unique identifier 167 for such
a biomarker measurement or data entry accordingly. In the case of
biomarker measurements, if the measurement is accepted as valid for the
request 240, the software 34 causes the processor 102 to prompt the user
to input additional information if needed by the structured collection
procedure 70 to provide context 252 for data resulting from the request
240. Such additional input, may include, for example, a rating of energy
level from 1 to 5, where 1 is low and 5 is high; meal size from 1 to 5
where 1 is small and 5 is large, and exercises from yes or 1 to mean over
30 minutes, and no or 2 to mean less than 30 minutes. Such additional
information or contextual information 156 when inputted via the user
interface 146 is stored by the processor 102 in the data file 145
associated with the unique identifier 167 for the data event request 240
requiring the additional information also in step 324.

[0158] In one embodiment, biomarker measurements determined by the
processor 102 as not being close enough in time to the data event request
240 defined by the structured collection procedure 70 will not be tagged
with a unique identifier 167 in the data file 145 by the processor 102.
Such is illustrated in the shown data file 145 with request 240d and data
values 256d not being associated with a unique identifier 167 e.g.,
<null>. An example of a definition of `close enough in time to the
collection procedure` as instructed by the structured collection
procedure 70 and/or software 34 to cause the processor 102 to make such a
determination may be defined as being relative to a prescheduled time or
a snoozed time. For example, for pre-prandial measurements up to 15
minutes in anticipation is acceptable; for post-prandial measurements, up
to 10 minutes in anticipation is acceptable; and for bedtime
measurements, up to 15 minutes in anticipation is acceptable. Other
definitions may be provided in other structured collection procedures 70
and/or software 34.

[0159] In step 326, the processor 102 then evaluates whether the exit
criterion 228 for the selected structured collection procedure 70 is
satisfied. If not, then the processor 102 continues with performance the
schedule of events 222 until the exit criterion 228 is satisfied. Upon
satisfying the exit criterion 228, the collection procedure 70 ends in
step 328. In one embodiment, the structured collection procedure 70 may
also end if in step 318, the entry criterion 226 is also not met.

[0160] In some embodiments, the structured collection procedure 70 can be
configured for performance as a paper tool 38; diabetes software 34
integrated into a collection device 24 such as a blood glucose meter 26;
diabetes software 34 integrated into the computing device 36, such as a
personal digital assistant, handheld computer, or mobile phone; diabetes
software 34 integrated into a device reader 22 coupled to a computer;
diabetes software 34 operating on a computer 18, 25 such as a personal
computer; and diabetes software 34 accessed remotely through the
internet, such as from a server 52. When diabetes software 34 is
integrated into a collection device 24 or a computing device 36, the
diabetes software 34 can prompt the patient to record diary information
such as meal characteristics, exercise, and energy levels. The diabetes
software 34 can also prompt the patient to obtain biomarker values such a
blood glucose values.

[0162] FIG. 8B shows a method of implementing the structured collection
procedure via a graphical user interface provided on a collection device
24, which when executed on the collection device, cause the processor 102
to perform the following steps. Upon pressing a certain combination of
the buttons 147, 149, the patient 12 can scroll to the structured
collection procedure 70 available for selection in a list 329 provided by
the processor 102 on the display 108 of the collection device 24 in step
330. If desiring to start the structured collection procedure, the
patient 12, for example, selects via pressing an OK button 151 in step
332, the desired structured collection procedure 70. In this example, the
entry criteria 226 (FIG. 6) of the structured collection procedure 70
provides information in step 334 which the processor 102 displays to the
user on the display 108. After reading the displayed information, the
user presses any button in step 336 in which the next procedure in the
entry criteria 226 is performed by the processor 102. In this illustrated
example, as part of the entry criteria 226, a question is then asked in
step 338 by the processor 102. If the patient 12 is still desirous of
starting the structured collection procedure, the patient 12 selects the
OK button 151 in step 340; otherwise, any other press via button 147, 149
will cause the processor to go back to the list 329, thereby stopping the
set-up procedure for the structured collection procedure 70.

[0163] After the patient 12 presses the OK button 151, the processor 102
in step 342 will provide on the display 108 an alarm clock 343 for
setting the time to begin the selected structured collection procedure
70. It is to be appreciated that all the required events 237 for
biomarker sampling, patient information, etc., is automatically schedule
by the processor 102 in accordance with the schedule of events 222 for
the structured collection procedure 70 in which timing, values,
questions, etc., therein may have been adjusted by the clinician 14 as
discussed previously above in reference to FIGS. 7A and 7B. Therefore,
other than entering the start time as permitted by the entry criteria
226, no other parameter adjustments in the structured collection
procedure 70 is required by the patient 12 (or permitted in one
embodiment).

[0164] In the illustrated embodiment, the patient in step 344 can adjust
the start time of the structured collection procedure for the next day,
e.g., Day 1, via buttons 147, 149. Upon confirming the start time in step
346 via pressing the OK button 151, the start time is recorded in memory
110 as part of the setup data 163 in the data file 145 (FIG. 4) for the
structured collection procedure 70 by the processor 102. The processor
102 then displays the selection list 329 on the display 108 in step 348,
thereby completing the set-up procedure, which satisfies the entry
criterion 226, and indicates on the display 108 that the collection
device 24 is in a structured testing mode 349.

[0165] It should be appreciated that in on embodiment multiple structured
collection procedures can be executed sequentially or simultaneously at
any given time, and hence in one embodiment the mode 349 provided on the
display 108 will indicated which structured testing is being performed.
However, in one embodiment, the software 34 does not permits the user to
schedule another structured collection procedure, unless the start date
is later than the end date of the current structured collection procedure
being executed via the user interface 146. It is to be appreciated that
processor 102 may re-schedule the following structured collection
procedures automatically if the current structured procedure is still
running due to the exit criteria 228 not being met. The software 34 in
another embodiment may also permit the user to override a scheduled date
for a structured collection procedure. If a structured collection
procedure is scheduled and the user enters the set mode function again,
the software 34 causes the processor 102 to display the scheduled date on
the display 108 as the default date; if the user exits the set mode
without modifying the date, the previously scheduled date stays active.
If a structured collection procedure has started, the software 34 permits
the user to enter the set mode and cause the processor 102 to cancel the
current structured collection procedure, if desired.

[0166] In step 350, an alarm condition 351 can be provided by the
processor 102 the next day (as indicated by the symbol Day 1) as was set
in the above-mentioned procedure the previous day (as indicted by the
symbol Start Up). Upon the user selecting any button 147, 149, 151 in
step 352, the processor 102 as instructed by schedule of events 222,
provides a first scheduled event 237 which is information 353 to be
displayed on display 108 in step 354, which the patient 12 acknowledges
with any button 147, 149, 151 being pressed in step 356. Next in step
358, the processor 102 is instructed by the schedule of events 222 to
execute a second scheduled event, which is to display on the display 108
a question 359 for the patient, which the patient 12 acknowledges with
any button 147, 149, 151 pressed in step 360. In the illustrated
embodiment, the patient in step 362 indicates the start time of breakfast
in minutes from the wake up alarm 351 previously acknowledged in step
352. Upon confirming the meal start time in step 364 to the processor
102, via pressing the OK button 151, the meal start time is recorded in
memory 110. For example, the meal start time is recorded in the data file
145 in the associated data record 152 as data for the event 237 by the
processor 102. Additionally, in step 366, the processor 102 displays to
the patient 12 the information regarding the timing for the next schedule
event as a reminder. In step 368, upon reaching the next scheduled event
indicted by the schedule of events 222, the processor 102 provides a
request 240 on the display 108 for the patient to take a measurement,
e.g., a blood glucose measurement. Additionally, in step 370, the
processor 102 also makes a request 240 for information on the size of the
meal that is to be ingested as required by the schedule of events 222 in
order to provide contextual information 156 to the measurement value.

[0167] As mentioned above previously, for each event the software 34
causes the processor 102 to assign a unique identifier (e.g. incremental
count) 167 (FIG. 4) to the data of each request 240 provided in the
schedule of events 222 which meet the adherence criterion 224 in the
associated date record 152 for the event 237. Therefore, while the
structured collection procedure is being executed, the software 34
permits the user to perform a measurement on the collection device 24 at
any time out side the schedule of events 222. Such a measurement since
not being performed according to a request 240 will not be evaluated for
the adherence criterion 224, and thus will not be provided with a unique
identifier 167 in the date file but will only be provided with a
date-time stamp and its measurement value. Such data is still recorded in
the data file 145, as such data may still be useful for another analysis.

[0168] In another embodiment, the software 34 also permits reminders for
biomarker measurements, such as provided in step 238. For example, in one
embodiment, the processor 102 provides an alarm and/or alert message for
a reminder via the indicator 148 and/or on the display 108, respectively,
to provide a measurement. For example, at the time 238 of a particular
request 240 for taking a biomarker measurement (or reading), the
processor 102 prompts the patient 12 by al least displaying on the
display the message, "It is now time for your reading." An audible alarm
and/or tactile alarm (vibrations) can be provided by the processor 102
via indicator 148 in another embodiment. For example, in one embodiment,
the collection device 24 will provide such a prompt even when already
powered on, such as by the patient 12 for another reason, e.g., to
conduct a non-scheduled event, when in, for example, a window of time in
which to take the requested measurement/reading, or even when powered
downed, such as in a standby mode, by waking up to provide the reminder
via the prompt. In another embodiment, the provided reminder or prompt
can be `snoozed` for a pre-defined period as mentioned above, that still
falls within the window of time in which to take the requested (critical)
measurement/reading such as for example, 15 minutes or any other such
suitable time that falls in the window of time. It is to be appreciated
that the snooze feature for a measurement/reading that is considered
critical to the structured testing procedure 70, e.g., a
measurement/reading needed for helping to address the medical use case or
question, needed to meet adherence criteria 224, and/or needed in
subsequent analysis for some determination, etc., the snooze feature will
not extend the request 240 beyond the window of time provided by the
collection procedure 70 via, e.g., adherence criterion 224 for the
request 240. For example, in one embodiment one or more events 237 in the
schedule of events 222 can be pre-defined as critical as well as being a
primary sample via use of the options parameter 232 (FIG. 7B) provided in
the structured collection procedure 70. For example, an event 237 which
is designated as critical is one that cannot be missed, but if missed can
be replaced by another sample already in the date file 145. In still
another embodiment, the snoozing can be up to a number of times, for
non-critical measurements. For example, certain events 237 in the
structured collection procedure 70 could be designated as having a
non-critical request 240, which can be snoozed, such as via selecting
such an option that is provided as one of the options parameter 232 (FIG.
7B). The options parameter 232 in this embodiment could for example
provide the snooze option as well as a selectable time interval (e.g.,
1-60 minutes, etc.) and a selectable number of times (e.g., 1-5, etc.)
that the user is permitted to snooze the request 240. In still another
embodiment, the collection device 24 permits for an alarm shut off i.e.,
the indicator 148 if providing the reminder (audible, vibratory) can be
shut off for the entire window of time via the user interface 146, but
wherein processor 102 still accepts the measurement/reading as long as it
is made in the window of time. In still another embodiment, the
collection device 24 provides a skip reading option also received by the
processor 102 via a selection entered using the user interface 146, e.g.,
from a list of selectable options, such as for example, snooze, alarm
shut off, skip reading, provided on the display 108, in which again no
reminder/prompt will be provided as patient 12 has indicated to the
processor 102 that he/she does not want to take that particular requested
measurement/reading. It is to be appreciated that selecting the skip
reading selection option can result in an adherence event 242 resulting
in further processing, such as discussed previously above in early
sections, if adherence criterion 224 had been associated with the event
237 prompting the request 240.

[0169] In still another embodiment, the adherence criteria 224 can require
biomarker measurements to be performed close enough in time to a data
event request 240. Therefore, if such biomarker measurements are
performed within the period specified by the adherence criteria 224, the
processor 102 can indicate that the measurements or data entry for the
event is acceptable and tags (i.e., assigns the unique identifier 167)
the value of the biomarker measurement or data entry in the data file 145
accordingly. In the case of biomarker measurements, if the measurement is
accepted as valid for the data event request 240 (i.e., meets the
adherence criterion(s) 224), the schedule of events 222 may causes the
processor 102 to prompt the user to input additional information if
needed by the structured collection procedure 70, such as mentioned above
regarding step 370 to provide contextual information 156 (i.e., context)
to the measurement received in response to a request 240.

[0170] Such contextual information 156 when inputted via the user
interface 146 can be stored by the processor 102 in the data file 145
associated with the unique identifier 167 for the data event request 240
requiring the additional information. Biomarker measurements determined
by the processor 102 as not being close enough in time to the data event
request 240 as defined by the adherence criteria 224 will not be tagged
in the data file 145 by the processor 102. Such is illustrated in the
shown data file 145 (FIG. 4) with data event request 240d and data values
256d not being associated with a unique identifier 167. An example of a
definition of `close enough in time to the collection procedure` as
instructed by the adherence criteria 224 to cause the processor 102 to
make such a determination may be defined as being relative to a
prescheduled time or a snoozed time. For example, for pre-prandial
measurements up to 15 minutes in anticipation is acceptable; for
post-prandial measurements, up to 10 minutes in anticipation is
acceptable; and for bedtime measurements, up to 15 minutes in
anticipation is acceptable. Other definitions may be provided in other
adherence criteria 224 for other events in the schedule of events 222 as
well as in other structured collection procedure.

[0171] In the illustrated embodiment, the user uses the buttons 147, 149
to scroll to a selection, which is entered by the processor in the data
record 152 for the associated request 240 via pressing Okay button 151 in
step 372. In one embodiment, the meal size can be indicated via a number
range, such as for example, from 1 to 5, where 1 is small and 5 is large.
In the illustrated embodiment, additional input for contextual
information 156 regarding a rating of energy level from 1 to 5, where 1
is low and 5 is high is requested in step 374, which is entered in the
data file 145 as mentioned previously above via the processor 102
receiving input for the request 240 by using the user interface 146 in
step 376. In other embodiment, other contextual information 156 may
include indicating whether the patient exercised and/or how long. For
example, the user interface 146 may be use in which yes or 1 to mean over
30 minutes, and no or 2 to mean less than 30 minutes. In the illustrated
embodiment, as the exit criterion 228 is now meet via successfully
performing steps 368-376, the structured collection procedure 70 ends in
step 378, wherein the processor 102 again displays the list 329, such
that the patient 12 may perform other tasks on the collection device 24
if so desired. Reference is now made to FIG. 9 hereafter.

[0172] Method of Contextualizing Biomarker Data

[0173]FIG. 9 depicts a method 388 of contextualizing biomarker data for
diabetes diagnostics and therapy support according to an embodiment of
the invention. It is to be appreciated that in the previous embodiments
discussed above with reference to FIGS. 8A and 8B, the contextual
information 156 was requested and recorded with the associated biomarker
value by the processor automatically during the structured collection
procedure 70. However, in embodiments where such automation is not
provided on the collection device 24, and the patient is using a paper
tool 38, the collection data can be later associated with its contextual
information 156 after, for example, the structured collection procedure
70 is performed in step 390 to create at least data event values 256. If
not already done by the collection device 24, such as in the case of a
device with limited memory and processing power or when recordings are
made on paper tool 38, such data may be provided to another one of the
devices 18, 25, 36 that is running the software 34 and has the ability to
associate at least the data event values 256 (FIG. 4) with their
respective data event requests 240. This associating of at least the data
event values 256 with their respective data event request 240, the
date-time stamp 169, and the contextual information 156 results in
contextualized (self-monitoring) data 170 in step 392.

[0174] It is to be appreciated that data as used in structured testing
according to the present invention deals with the prospective collection
of contextualized data. Considering FIG. 10A, in this example, the
inherent advantage of context becomes clear when one considers the
utility of having a subway map on the left-hand side without context and
one on the right-hand side with context, which makes it possible to
easily navigate the system and travel from one place to another. In a
similar manner, contextualization can play an important role in diabetes.
Context associated with data, for example, can be due to therapy, an
event (such as meals, exercise, an event 237, request 240, etc.), and
time of request for data collection itself (e.g., timing 238). As such,
any data collected by the patient with measured values can be
contextualized by being associated with one or more the above mentioned
factors e.g., therapy, events, and time, each of which are discussed
further hereafter.

[0175] Therapy can be defined, for example, as an on-going treatment
intended to alleviate the patient's impaired glucose control. This
treatment generally involves anti-diabetic agents such as insulin, oral
medications, and diet and exercise. A therapeutic (or a therapeutic
combination) has a specific pharmacodynamic effect on a patient's
glycemia owing to different mechanisms of action. A change in either the
dose(s) of the therapeutic(s) or a change in the therapeutic(s) itself,
will lead to a change in the patient's glucose control. Consequently, the
collected bG data is strongly linked to underlying therapy and dose and
this information is used to contextualize the data. A change in dose or
therapeutic will lead to a different context. It is to be appreciated
that the therapy context can be set by the clinician 14 in consultation
with the patient at the time of designing the collection procedure 70,
such as discussed previously above with regards to FIG. 5A.

[0176] In one embodiment, the events 237 in a collection procedure 70 can
include specific conditions around bG measuring points that play a role
in altering the patient's normal glucose levels. As mentioned previously
above, events 237 can be meal or exercise based, and are pertinent for
data contextualization. In this context, the underlying assumption is
that the patient operates, more or less, under a well-defined schedule.
At the time of creating the collection procedure 70, the patient 12 can
discuss lifestyle events with the clinician 14 so that the collection
procedure 70 can be tailored according to the needs of the patient 12. As
an example and with reference to FIG. 10B, consider a typical collection
procedure 70 whereby the patient 12 does not exercise regularly so that
the majority of the events are meal based events that consist of
breakfast, lunch, and dinner. Such a lifestyle of the patient 12 leads to
six candidate points for bG measurement (pre and post for each of the
meals) for the schedule of events 222 in the collection procedure 70.
During the process of creating/customizing (FIG. 5A and/or FIG. 7B) of
the collection procedure 70, the clinician 14 may specify that the
patient collect one or more or all of these points as per the schedule of
events 222 of the collection procedure 70. Any data collected in addition
to these points, i.e., outside the requirements of the collection
procedure 70, can be classified as non-collection procedure readings by
the processor 102. In a similar manner, for a Type 1 diabetic patient
that exercises regularly, the clinician 14 can tailor/customize a
collection procedure 70 to include additional measurements around the
exercise event. The event information, in this example, is then used to
contextualize the data in an appropriate manner depending on the event
237.

[0177] Time represents the actual time at which a measurement is made and
is in absolute terms, e.g., date-time stamp 169 (FIG. 4). Additionally,
time can also be represented in terms of deviations, i.e., offset from a
particular event. As an example, a postprandial reading is taken at a
specific time after a meal and this time may be different across
different days. This scenario arises as the patient may not be able to
take an event based reading t the same time every day. Consequently,
there is a distribution of times at which the same measurement has been
made at different days. The knowledge of this distribution can become
useful for analysis of such timing as well as the parameter timing 238 in
the collection procedure 70.

[0178] Additionally, with the contextualized data 170, the physiological
state of the patient 12 at the time of the measurement can be described.
The patient's physiological state can influence a biomarker value, so
knowledge of the patient's physiological state aids in the understanding
of a biomarker value. The biomarker data can be contextualized because
the biomarker data is collected in the context of predetermined events
such as last time of meal, meal type, meal distribution, exercise
information, sleep quality, sleep duration, waking time, and stressors
such as illness and the like. Time-resolved data permits interpreting the
biomarker data in context with other information, such as compliance with
a structured collection procedure 70 and patient lifestyle events.

[0179] Referring again to FIG. 9, the contextualized data 170 is evaluated
using adherence criterion (or criteria) 224 to generate accepted
contextualized data 395 that meets the adherence criterion 224 in step
394. As the adherence criterion 224 can provide a basis for comparison of
a data event value 256 with a standard, so the data event value can be
either accepted and used or rejected and not used, the adherence criteria
224 can be used to filter data in one embodiment. In another embodiment,
step 394 may precede step 392.

[0180] FIG. 11, for example, shows a diagram of accepted contextualized
data 395 intermingled with non-acceptable contextualized data 397. The
diagram vertical axis shows biomarker values 256 including context 252 in
the form of a biomarker setpoint, a biomarker upper limit, and a
biomarker lower limit. The diagram horizontal axis shows performance
times 238 of measurement requests 240 and a sleep period event 237 in
which the actual sleep surpassed a recommended minimum amount of sleep as
indicated by the dashed line. The accepted contextualized data 395 is
that which met the adherence criterion 224. The non-acceptable
contextualized biomarker data 397 are either not within the structured
collection procedure 70 or did not meet adherence criterion 224. By
excluding the non-acceptable contextualized biomarker data 397, the
accepted contextualized biomarker data 395 can help improve
decision-making. Statistical techniques can be used to view the accepted
contextualized biomarker data 395 in a form that conveys additional
information to a clinician 14. Examples of statistical techniques include
regression methods, variance analysis, and the like. Hereafter further
details about another embodiment of the software 34 are provided.

[0181] Software

[0182] As mentioned above in previous sections, the software 34 can
operate on the patient computer 18, the collection device 24, a handheld
computing device 36, such as a laptop computer, a personal digital
assistant, and/or a mobile phone; and paper tools 38. The software 34 can
be pre-loaded or provided either via a computer readable medium 40 or
over the public network 50 and loaded for operation on the patient
computer 18, the collection device 24, the clinician computer/office
workstation 25, and the handheld computing device 36, if desired. In
still other embodiments, the software 34 can also be integrated into the
device reader 22 that is coupled to the computer (e.g., computers 18 or
25) for operation thereon, or accessed remotely through the public
network 50, such as from a server 52. Additionally, one or more
collection procedures 70 can be provided as part of the software 34,
provided as updates to the software 34, or provide as individual files
which can be operated on and used by the software 34.

[0183] In the embodiment discussed hereafter, the software 34 runs on the
collection device 24 and provides three basic elements: one or more
structured collection procedures 70, data file 145, and one or more
scripts. As the features of the structured collection procedure 70 and
data file 145 are the same as previously discussed above no further
details is provided. The one or more scripts are small independent
programs that reside on the collection device 24 and each can perform a
specific set of tasks. Such scripts can include a protocol script 401, a
parse script 403, and an analysis script 405 such as depicted by FIG. 12,
each of which are discussed in detail in the following paragraphs.

[0184] Protocol Script

[0185] The protocol script is a script that actually enables the execution
of the collection procedure 70 by the processor 102 on the collection
device 45. At the time of initiation of collection procedure 70, the
protocol script in one embodiment causes the processor 102 to create a
data structure that outlines the amount of data expected as outlined by
the collection procedure 70. In another embodiment, the data structure
can have a variable size, or be a fixed size but with a buffer e.g., an
array in the data structure, should additional data be collected during
the collection procedure 70. For example, such have buffer can account
for situations when the collection protocol 70 can be extend, if desired,
or needs to be extended due to not meeting a desired condition, e.g., a
patient biomarker value has not reached a desired value, such as, for
example, up to a maximum size of allocable memory for the data structure
in memory 110 of the collection device 24. This data structure, such as
data file 145, stores at a minimum the time of initiation of the
collection procedure 70, actual measurement of biomarkers, such as data
event value 256, and time of the measurements, such as date-time stamp
169, and optionally all other information used for additional
contextualization, such as the contextual information 156, and request
240, such as meals, exercise, etc. As an alternative embodiment, one can
also consider the data structure to be a calendar that is generated by
the clinician 14 which can include details in terms of the day, and the
time of day when a measurement needs to be made. This calendar feature
also enables the patient to see readily when he has to make the next
measurement. The protocol script also causes the processor 102 to perform
all of the functions necessary for the processor 102 to execute the
collection procedure 70. Once appropriate data is collected, e.g., a
successful run of the collection procedure 70, the protocol script causes
the processor 102 to mark the data structure with a completion flag 257
in one embodiment or provides it as state condition of the software 34 in
another embodiment and passes control of the processor 102 as provided in
the software 34 to the parse script. In the former embodiment, the
completion flag 257 can also be used to provide information regarding the
reason for ending/terminating, such as to identify the type of completion
(end, logistical (timeout), adherence terminated, etc.). For the latter
embodiment, as one or more structured collection procedures 70 may be
loaded onto the collection device 24 at the factory as mentioned
previously above, providing state conditions for each collection
procedure 70 in the software 34 helps to support the requirement that the
procedure only be available after authorization by the clinician 14. In
one embodiment, such state conditions of each collection procedure 70 can
be tracked by the software 34 and can include one or more of a `Dormant`
state, an `Authorized` state, a `Pending` state, an `Active` state, and a
`Completed` state. The Dormant state is useful when the collection device
24 is shipped with one or more embedded collection procedures 70, but
until authorized for use, such as described above previously, cannot be
use (or seen) by the patient 12 on the collection device 24. In this
case, the collection procedure 70 is said to be in a Dormant state. The
Authorized state is when the collection procedure 70 becomes usable after
the clinician 14 authorizes it for use on the collection device 24.
During this state, the collection procedure 70 can be configured (e.g.,
by the clinician) and initiated for start as also configured, e.g., via
selection by the clinician, the patient 12, or by a start date. The
Pending state is when a start date is set, but prior to execution, e.g.,
in which the collection procedure 70 is waiting for some unknown time
until the entry criterion 226 is met before executing the schedule of
events 222. Once the collection procedure 70 begins executing on or after
the start date, via meeting the entry criterion 226 in one embodiment,
the collection procedure is said to be in the Active state in which at
least the schedule of events 222 is being implemented by the processor
102. The Completed state functions in a similar manner as to the
completion flag 257 when the collection procedure 70 has ended as
mentioned above previously.

[0186] Parse Script

[0187] The parse script is the script that causes the processor 102 to
parse the contextualized data, such as e.g., contextualized data 395
(FIG. 11), once the collection procedure 70 data collection is complete.
The parse script causes the processor 102 to try to resolve any
exceptions (e.g., in real time, i.e., as the procedure 70 is being
executed) that may have arisen at the time of execution of the collection
procedure 70, e.g., for only critical data events 237 in the collection
procedure 70 (e.g., a mandatory data collection for a biomarker value) in
one embodiment. If at the end of the execution of the parse script
exceptions remain for at least the mandatory data required for the
collection procedure 70, then the parse script will cause the processor
102 to signify that appropriate data has not been collected.
Consequently, the collection procedure 70 is marked by the processor 102
as incomplete via the completion flag 257 not being provided by the
processor 102 in the data file 145. If there are no exceptions at the end
of a parse script, e.g., at least for the critical events in one
embodiment, and/or events designated as primary samples in another
embodiment, and/or for all events in still another embodiment, the
collection procedure 70 is marked complete via the processor 102
providing the completion flag 257 in data file 145, which contains the
collected and contextualized data. The role of the parse script will be
explained hereafter subsequently in a still another embodiment
illustrating an execution stage.

[0188] Analysis Script

[0189] The analysis script causes the processor 102 to analyze the
completed collection procedures 70 that have their own associated
datasets, e.g. data file 145. The analysis performed by processor 102
according to the analysis script can be simple (mean glucose value,
glucose variability, etc.) or it can be more complex (insulin
sensitivity, noise assessment, etc.). In one embodiment, the collection
device 24 can perform the actual analysis itself, or the analysis can be
carried out on a computer, such as computer 18, 25. In one embodiment,
the results from the analysis script can then be displayed either on the
display 108 of collection device 24 by the processor 102 or on the
display of a peripheral device. Reference to the scripts and program
instructions of the software 34 are discussed hereafter with reference
made to FIGS. 13 and 14 as well as to FIGS. 2 and 5B.

[0190] Collection Procedure Execution

[0191] FIGS. 13 and 14 depict a collection procedure execution method 400
performed by the processor according to the program instructions of the
software 34 using the above mentioned scripts during a collection
procedure 70. The dash-dot lines indicate the boundary between the
different domains of the different scripts and are the boundaries across
which exchange in control takes place. It is to be appreciated that the
hereafter disclosed embodiments of the present invention can be
implemented on a blood glucose measuring device (such as a meter) that
has the capability to accept one or more structured collection procedures
70 and the associated meter-executable scripts discussed above.

[0192] With reference first to FIG. 13, once a collection procedure 70 is
initiated on the collection device 24 by the processor 102 using the
protocol script 401 in step 402, such as in any of the above manners
discussed previously above in earlier sections, after meeting entry
criterion 226 (if provided in the collection procedure 70), a data event
instance, e.g., an event 237, occurs according to the schedule of events
222 in step 404. For the event 237, in this example, the processor 102
prompts via a request 240 for the patient 12 to take a reading around a
lunch event as mandated by the collection procedure 70. For example, the
prompting of the request 240 may be an alarm provided by the processor
102 via indicator 148 that goes off, whereby the patient 12 is asked also
on the display 108 by the processor 102 to take a reading. In one
embodiment, the snooze feature as well as the skip reading feature are
provided by the software 34, where the patient 12 can use the user
interface 146 to enable a delay or to skip the data collection. For
example, selecting the delay feature as discussed previously above in
earlier sections can cause the processor 102 to prompt the patient 12
again for the event 237 a predefine amount of time after enabling the
delay to the data collection. For example, such a feature could be used
in case the patient 12 cannot take the reading at the time of the
prompting in one embodiment, e.g., at the beginning of the window of time
in which to provide the measurement/reading. Likewise, the skip feature
would be selected if the patient believes he/she cannot perform the
measurement/reading within the window of time. An example of a window of
time or a specific time-window around an event is shown by FIG. 10B
("allowable window").

[0193] The processor 102 according to the protocol script 401 then uses
adherence criterion 224 in step 406 to determine whether the data
collection for the event 237 was successful by meeting the conditions of
the adherence criterion 224 in one embodiment. For example, a successful
data collection will occur if the patient 12 successfully collects the
data within the specified time-window. In another embodiment, the same
processing may be applied to one or more sampling group 262. Successfully
collected data for such events in the schedule of events 222 and/or
sampling grouping 262 is then contextualized by processor 102 according
to the protocol script 401 in step 410, for example, by associating in
the data file 145 with the collected data, e.g., data 256, the current
time e.g., the date-time stamp 169 (FIG. 4), the event 239 and/or request
240, and available contextual information 156, e.g., about the patient's
therapy as well as the unique identifier 167, if needed, as discussed
also previously above in earlier sections.

[0194] If, in the above example, the patient 12 fails to collect data
within the specified time-window, then in step 412 the processor 102
according to the protocol script 401 scans the contextualized data
resident on the collection device 24 to determine if a similar data-point
is available that meets the requirements of the missed data-point. This
data-point will be selected by the processor 102 according to the
protocol script 401 in step 414 only if it fulfils all requirements of
the data-point intended to be collected.

[0195] As an example, if the collection procedure 70 requires a paired
measurement, i.e., pre- and post-meal measurements, then it is important
for both of these measurements to be made around the same event. In this
case, substitution of any one value from a prior value is not
permissible; should such occur, an exception is marked for the event
under consideration. In this scenario, the pertinent element in the
data-structure is incomplete at that location wherein the processor 102
in step 416 will declare an exception, such as providing a <null>
value to the unique identifier 167 in the specific data record 152 for
the event 237 which caused the exception. Should no such constraint
exist, then a data-point from the data resident on the collection device
24 can be selected by the processor 102 in step 414 and added to the
contextualize collected data in step 410. This substitute data-point will
have the same contextual information, event context, and collected within
a specified time-window of the original collection period if such is a
requirement. In step 418, according to the protocol script 401, the
processor 102 will check to see data collection is completed for all of
the events 237 in the schedule of events 222 of the collection procedure.
The processor 102 also checks whether exit criterion 228 is met, if such
is provided by the collection procedure 70. If not, then the processor
102 proceeds with the next event in the schedule of events 222 by
returning to step 404 wherein the data collection then proceeds for the
remainder of the collection procedure 70 in a similar fashion. It is to
be appreciated that frequent messages as part of the guidance 230 of the
collection procedure 70 can be displayed by the processor 102 to the
patient 12 on the display 108 to guide the patient throughout the entire
data collection. It is to be appreciated that as part of the protocol
script that whenever any specified exit criteria is met, the processor
102 can end the collection procedure 70 in one embodiment or present as
an option on the display 108 for the patient to select ending the
procedure 70 in another embodiment. Once the data collection is completed
in step 418, the protocol script 401 then hands over control of the
processor 102 to the parse script 403 in step 420.

[0196] With reference to FIG. 14, which highlights the role played by the
parse script 403, when control is passed upon completion of the
collection procedure 70, the parse script 403 checks the contextualized
data 170 in the data file 145 for incompleteness. To accomplish this, the
processor 102 reads the contextualized data 170 from memory 110 in step
422 and looks for any exceptions (e.g., <null> value for any unique
identifier 167) provided in the data file 145 as an exception check in
step 424 according to the parse script 403. When possible, the processor
102 tries to address any these exceptions using data available on the
collection device 24 should it be possible in step 426. As an example,
applicable data either may be available from non-collection procedure 70
events or from data collected as part of another collection procedure 70.
If the exception cannot be addressed from existing data, then in step 428
the collection procedure 70 is marked incomplete. At this point the
completion flag 257 for the collection procedure 70 is set as incomplete
(e.g., not set, <null>, a pre-define value, etc.). Otherwise, if
there are no exceptions and/or all exceptions have been addressed in step
426, then the processor 102 sets the completion flag 257 as completed and
then can display the result of the collection procedure 70 in step 430.
The processor 102 in accordance with the parse script 403 then collects
all of the data associated with the collection procedure 70 (i.e., data
file 145) and hands control over to the analysis script 405 in step 432.

[0197] In step 434, the analysis script will cause the processor 102 to
perform all the necessary analysis, such as analysis 258 (FIG. 6B) that
is detailed in the collection procedures 70, on the data collected in
step 432, if the completion flag 257 is marked complete in the data file
145. In one embodiment, simple analysis routines calculations can be
performed on the collection device 24, whereas more complex collection
procedures 70, the analysis can be done on a computer, such as computer
18 or 25.

[0198] When a collection device 24 containing one or more collection
procedures 70 is connected to a device reader 22, such as the Smart-Pix
device, that is connected to computer 18 or the clinician computer 25,
the software 34 cause the associate processor to display automatically a
list of the completed collection procedures 70 and their associated data
files 145.

[0199] In one embodiment, the software 34 can interact with the device
reader 22, such as provided as a SmartPix device, for visualization of
results, or with any other device including computer 18, 25, etc., that
can display the results of the analysis of the data from the collection
procedure 70. At this point, if on the clinician computer 25, the
clinician 14 can decide to view the results of completed and analyzed
collection procedures 70 or carry out analysis of completed collection
procedures 70. The clinician 14 can also review any collection procedure
70 that did not complete and try to evaluate the exceptions that exist in
the collection procedure 70. This interaction gives the clinician 14 an
opportunity to give the patient feedback on his data and/or evaluate
reasons for the failure to complete existing collection procedure(s) 70.

[0200] Use Case Example

[0201] Referring to FIG. 15, a use case example is provided which
highlights a sequence of actions carried out by the clinician 14 as well
as the patient 12. This sequence encompasses an overview of the clinician
14-patient 12 interaction from the formulation of the medical question to
the completion of the collection procedure 70. The dash-dot line
indicates the boundary between the clinician 14 and patient 12 domains
and it is the boundary across which information exchange takes place. The
discussion on the completed collection procedure 70 also serves to
encourage the patient and provides the clinician 14 with an opportunity
to provide feedback on patient performance and progress.

[0202] In step 440, patient visits the clinician 14 and in step 442, the
clinician identifies a problem, which results in the selection of medical
use case (medical question) in step 444. After selecting the medical
question, such as on computer 25, the clinician uses the computer to
select and define/customize the structured collection procedure 70 in
step 446 using method 200 and/or 300 (FIGS. 5A and 7A). After prescribing
the structured collection procedure 70, the computer 25 provides the
structured collection procedure 70 to the collection device 24, which is
received in step 448. The patient 12 starts the data collection according
to the structured collection procedure 70 using the collection device 24
after satisfying the entry criterion 226 provided in the procedure 70 in
step 450. During the data collection in step 452, events 237 are
automatically scheduled by the collection device 24 in accordance with
the scheduled of events 222 contained in the structured collection
procedure 70. Adherence criterion 224 is applied to at least to all
biomarker measurements, which are evaluated and recorded for meeting the
adherence criterion automatically by the collection device 24. In step
454, the structured collection procedure 70 is completed once the exit
criterion 228 is met. Next in step 456, any available collection device
based analysis 258 may be performed by the patient 12 if desire. Next in
step 458, a report may also be generated, such as the data report
mentioned in step 434 (FIG. 14). In step 460, the data (e.g., the
complete data file 145) either from the collection device 24 or from the
patient computer 18 is preferably sent to the clinician computer 25. The
collected data is received in step 460, is then analyzed in step 462.
Next, in step 464 a report can be generated, which may be used to
facilitated a discussion of any additional result in step 466 with the
patient 12. Next, documentation is printed in step 468, which can be
given to the patient 12 in step 470 as well as recorded (stored) in an
electronic medical record of the patient 12 in step 472.

[0204] Embodiments of the present invention also enable the generation,
modification, and transfer of collection procedures 70 to and from a
structured testing enabled device, such as collection device 24. As the
collection procedures 70 stem from and aim to address specific medical
use cases or questions, the transfer of the resultant information e.g.,
data file 145, from one device to another is carried out in a secure
manner. Additionally, a method whereby all of the collection procedure
related information (e.g., data file 145) for a patient or a group of
patients can be managed in a secure and efficient manner.

[0205] It is to be appreciated that the discussion provided hereafter
includes aspects related to the interaction between the clinician 14 and
the patient 12 as discussed previously above concerning FIG. 15. In
particular, the disclosure hereafter provides details regarding the
infrastructure required to manage the generation, transfer, and analysis
of the collection procedures 70. Reference hereafter is also made to the
system 41 of FIG. 2, as aspects pertaining to the transfer of devices and
information (data, reports, etc.) to and from the devices 18, 25 and 52
are provided.

[0206] In one illustrated embodiment, the system 41 can comprise server 52
being a web-server that serves as a repository of a plurality of
collection procedures 70a, 70b, 70c, 70d, as software 34 that resides on
the clinician computer 25, and the collection device 24, such as provided
as a blood glucose meter. Henceforth these components are referred to as
the "server", "software", and the "meter" respectively. Additionally, the
computer 25 where the software 34 resides is termed as the "client".

[0207] In one embodiment, the server 52 can serve as a central repository
for a number of collection procedures 70a, 70b, 70c, and 70d that address
specific medical questions. Accordingly, one or more collection
procedures 70 can be downloaded from the server 52 to the clinician
computer 25. In such an embodiment, all communications between the server
52 and the client computer 25 is done in a secure and web-based format.
Additionally, in another embodiment, there is no full two-way data
transfer between the computer 25 and the server 52 such that patient data
can never be transferred to the server 52. Furthermore, in other
embodiment, a request for a collection procedure from the server 52 can
be made only with a valid identifier. Such an embodiment ensures that
only authorized clients are allowed to access the server 52 to download
the requested collection procedure(s) 70.

[0208] In one embodiment, each collection procedure 70 downloaded from the
server 52 can be used only once (e.g., if the completed flag or state is
set, the procedure 70 cannot be run again until reauthorized by the
clinician 14). Each successive download of the collection procedure 70
requires access from an authorized client user with a valid ID 71 (FIG.
2). The server 52 also provides the client computer 25 with updates
thereby ensuring that the software is the most recent version. There also
exist restrictions on the communication from the client computer 25 to
the server 52. The server 52 can only access information related to the
installed version of the software 34. It is not possible for the server
52 to access any data resident in the client database e.g., memory 78.
Additionally, the data on the client computer 25 is access controlled so
that it cannot be used and accessed without the necessary permissions.

[0209] The software 34 residing on the client computer 25 serves as the
interface between the server 52 and the collection device 24. The
software 34 at the front end includes a user-friendly interface that
provides the clinician 14 with ready information pertaining to the
overall practice. This information may include details about all assigned
patients, details about the patients the clinician 14 is scheduled to see
on a given day, as well as the details about patients that need extra
attention. The software 34 also interfaces with a database that includes
relevant patient data that is arranged by an individual patient ID, such
as used by and provided in the healthcare record system 27. The software
interface also allows the clinician 14 to access the patient 12 details
using the patient identifier. In this manner the software 34 provides the
clinician 14 with information about the collection procedure(s) 70 that
the patient 12 has already completed (i.e., those with a completed set
for the completion flag 257), the associated results, and also the
collection procedure(s) 70 that the patient 12 is currently performing.
All of the data residing on the client computer 25 is secure and
access-controlled. The server 52 has no means to access the data. The
clinician 14 can access data from all patients in the practice. In
addition, an individual patient 12 can access his data, such as from a
server of the clinicians, using his patient identifier in a secure
web-based format. This data is downloaded to the database on computer 25
from the collection device 24 and associated to the patient 12 using the
patient identifier.

[0210] At the time of data download from the collection device 24, the
software 34 also performs an analysis on the data to ensure that the
integrity of the data is maintained and no corruption in the data has
taken place at the time of transfer. The client computer 25 with the help
of the software 34 can also send emails to the individual patients and
these emails can contain information about an upcoming appointment,
reminders on what the patient is supposed to do after an appointment and
reports that are results of a completed collection procedure 70. When the
clinician 14 downloads a collection procedure 70 from the server 52 for a
particular patient, the collection procedure 70 is associated with the
patient identifier. In this way, it is possible to account for what
collection procedures 70 are currently underway for his patients.

[0211] A downloaded collection procedure 70 can also be modified by the
clinician 14 using the software 34 to tailor the collection procedure 70
to individual patient needs as previously discussed above in earlier
sections (FIG. 7B). At the time of modification of the collection
procedure 70, the clinician 14 also has the option to alter the analysis
that will be carried out on the modified collection procedure 70.
Additionally, even for standard collection procedures 70 that have not
been modified, the clinician 14 has the option to add additional options
for analysis.

[0212] Furthermore, the clinician 14 can decide and set guidelines as to
when the procedure 70 must terminate. For example, the clinician 14, can
decide and set how many adherence violations are allowed, i.e., how many
measurements the patient can miss, such as via using the options
parameter 232 in the collection procedure 70.

[0213] In one embodiment, once a collection procedure 70 is introduced
into the collection device 24 by the clinician 14 (details discussed in
the next section), the collection procedure 70 cannot be altered by the
patient 12. Additionally, the collection procedure 70 is associated with
both the clinician 14 (the prescriber) and the patient identifiers to
ensure accounting of the collection procedure 70 and associated data
(e.g., data file 145).

[0214] The software 34 also allows the clinician 14 to select the type of
report that will be generated once the completed collection procedure 70
has been analyzed. This report is tailored for the device on which it
will be viewed. The report could be for a mobile device such as a
telephone, a palm device or a meter, or a computer, or a printed format.
The software 34 also has the ability to connect with an electronic
medical records system to add patient data and results of analysis
performed on the data from a collection procedure 70 to the medical
records.

[0215] The collection device 24 serves as the mechanism by which
prospective and contextualized data is collected by the patient 12 as
recommended by the collection procedure 70. The collection device 24 can
be owned by the patient or it can be owned by the clinician 14 and loaned
to the patient 12 for the duration of the data collection associated with
the collection procedure 70. The clinician 14 can introduce the
collection procedure 70 into the collection device 24 by a number of
mechanisms. For example, the collection procedure 70 can be downloaded
from the server 52 and added to the collection device 24 via a connecting
cable that links the client computer 25 to the collection device 24 in
one embodiment. The collection procedure 70 can also be obtained in
another embodiment on a chip (e.g., computer readable medium 40) that can
be inserted into the collection device 24. This collection procedure 70
is then loaded into firmware of the collection device 24 where it can be
initiated by the patient 12. The collection procedure 70 can also be
introduced using an RFID tagged chip (e.g., computer readable medium) in
still another embodiment.

[0216] Along with the downloaded collection procedure 70, the collection
device 24 also has the ability to display instructions to the patient 12
that guide the patient at the time of data collection. Additionally, as
discussed above, the collection procedure 70 can introduce into the
collection device 24 both the patient identifiers as well as the
clinician identifier. Similarly, the data collected from the collection
device 24 can be associated with the patient identifier and clinician
identifier, such as part of setup data 163 (FIG. 4) in the data file 145.
Additionally, the setup data 163 in the data file 145 can include
information about the collection device 24 (i.e., measurement noise,
calibration data), as well as strip lot numbers and other information
about the strips used for any data collection event 237. Such information
may be helpful at the time of data analysis.

[0217] At the completion of the collection procedure 70 the collection
device 24 can be connected to the software 34. At that time data, such as
data file 145, is transferred securely and stored by the processor 76 of
the client computer 25 according to the software 34 running thereon. Once
the analysis performed on the data from the collection procedure is
completed by the software 34 on the client computer 25, the computer 25
also has the ability to store results of the analysis for patient
reference. Reference is now made to FIGS. 16-18 hereafter.

[0218] Software GUI

[0219] In one embodiment, a typical workflow highlighting further features
of the software 34 useable through a graphical user interface (GUI 500)
provided thereby on a computer, such as computer 25 and/or server 52, are
presented. In this example, the typical scenario is when the clinician 14
opens the case file for a particular patient is considered. As shown in
FIG. 16, the clinician 14 can readily visualize important details about a
displayed patient file 502 using the GUI 500 of the software 34 running
on the client computer 25. On a top pane 502 of the GUI 500, the
clinician 14 can see and use various administrative tasks 504, such as
changing the displayed patient file, create an email containing
information form the patient file, create a fax containing information
from the patient file, save the patient file, bookmarking data in the
patient file, select existing bookmarks, print information/graphs from
the patient file, etc.

[0220] On a left pane 506 of the GUI 500, the clinician 14 has additional
options 508 such as the option to download patient data, such as data
file 145, when a collection device 24 is connected to the computer 25 or
18 (wired or wirelessly). The other options 508 also can also include
viewing details regarding a patient profile, logbook, and additional
records, and graphs based on calculated data, etc. As indicated by FIG.
16, the summary option is selected, which shows its content in a main
pane 510.

[0221] The main pane 510 indicates all of the typical steps in a workflow
for therapy administration for the patient 12. These steps can include
the following: Disease State 512, Therapy Selection 514, Therapy
Initialization 516, Therapy Optimization 518, and Therapy Monitoring 520.
Each step provided as an icon on the GUI 500 is discussed hereafter.

[0222] Disease State 512 is a determination of the disease state, e.g.,
the patient is a Type 1 or a Type 2 diabetic. Typically, the disease
state determination is carried out when the patient 12 first visits the
clinician 14 or when the clinician 14 suspects that a particular patient
might be at risk. Therapy Selection 514 follows thereafter once the
disease state is determined, and the clinician 14 needs to select an
appropriate therapy that takes into account the patient's disease state.
As Therapy selection 514 can include the processes of methods 200 and 300
shown by FIGS. 5A and 7A, respectively, no further discussion is
provided. Therapy Initialization 516 is the process of therapy
initialization involves establishing the initial details by means of
which therapy is administered to the patient 12. This may include details
about the starting dose of the therapy, time when the therapeutic is
taken, and the likes. Further details about Therapy Initialization 516
are provided hereafter in reference to FIG. 17. Therapy Optimization 518
involves the determination of the best effective dose for the patient
such that it will not cause side effects. Finally, Therapy Monitoring 520
involves routinely monitoring the patient 12 to detect therapy
obsolescence after the selected therapy has been optimized. Thus, the GUI
500 provides the clinician 14 with all of the useful information in a
user-friendly format.

[0223] FIG. 17 represents the scenario when the clinician 14 has already
determined the disease state and selected a therapy, via Disease State
512 and Therapy Selection 514, and is at the step for Therapy
Initialization 516. As shown, the software 34 shades in the GUI 500 the
steps already completed wherein only the step currently underway, e.g.,
Therapy Initialization 516, is highlighted. In addition, in one
embodiment, the software 34 does not permit the clinician 14 to progress
to the next step without accomplishing all the required actions in the
current step (in other words, all previous steps have been accomplished).
However, the software 34 provides the clinician 14 with the option to go
back and modify prior steps via selecting the particular icon for the
step in the GUI 500.

[0224] In this example, the patient 12 is diabetic, and currently for
Therapy Initialization 516 the clinician 14 needs to initialize a long
acting insulin therapy for a Type 1 diabetic patient. As shown, the
clinician 14 is presented on the GUI 500 for this step with all available
initializing options 522 for initializing the therapy. For example and as
shown, the clinician 14 can select a type of drug 524, such as show as a
long acting basal insulin, and select procedure selection icons 526
associated with the drug 524 and each associated with a collection
procedure 70 that is available for addressing a therapy question(s)
regarding a particular drug (e.g., Lantus, Levemir) listed associated
(and available) with the type of drug 524. The software 34 through the
GUI 500 also permits the clinician 14 to decide if additional therapy
related parameters 528, such as insulin sensitivity, insulin to
carbohydrate ratio, and the like, should be undertaken if such is needed.
Additionally, further details for the therapy initialization can be
viewed via selecting an icon for general information 530.

[0225] When the clinician selects one of the procedure selection icons
526, the software 34 provides a snapshot 532 of the conditions set in the
associated collection procedure 70, such as illustrated by FIG. 18.
Typical initial conditions provided in the snapshot 532 can include:
frequency of dosage (dosing adjustment), (default) starting dose, target
levels, schedule of events (e.g., Measure fasting blood glucose for 3
days), recommendations for computation (e.g., modify drug dose base on
the 3-day median, measure remaining for days to assess the effect), and
the like. If more details regarding the selected collection procedure 70
are desired, such as related medical literature, case studies that may
have formed the basis for the structured testing procedure, and the like,
can be viewed via More Detail icon 534. The clinician 14 has also the
choice to either accept the collection procedure 70 as provided, via the
Accept icon 536 or suggest modifications to the collection procedure 70
via the Modify protocol 538. As selecting the Modify protocol 538 can
open on the GUI 500, for example, a screen representation of all the
parameters in the procedure 70 for modification, such as depicted by FIG.
7B, and as such was previously discussed above in earlier sections no
further discussion is provided. Once modifications are made to the
collection procedure 70, the clinician 14 can review and accept the
changes. Upon accepting the collection procedure 70, via selecting the
Accept icon 536 on the GUI 500, the software 34 cause the processor e.g.,
processor 76, to send the completed collection procedure 70 to the
collection device 24 as discussed previously above in earlier sections.
Certain advantages of the above mentioned embodiments of the present
invention are noted hereafter.

[0226] Although not limited thereto, the embodiments of the present method
offer the following noted advantages. Certain embodiments enable
contextualization of collected data by taking into account factors such
as meals and existing medications. All of the data analysis can be
carried out on prospective data, i.e., contextualized data collection is
carried out keeping in mind the medical question that needs to be
addressed. The collection procedures 70 are each geared towards
collecting bG data to address a specific medical issue, e.g., control of
postprandial glycemic excursions, regulating the fasting blood glucose
value, characterizing the patient insulin sensitivity, monitoring the
patient's therapeutic response, and the like. Using such collection
procedures, makes the task of collecting BG values goal oriented as the
patient knows the reason why he or she is carrying out such tests. It is
believed that awareness of the reason for conducting tests would lead to
an increase in adherence.

[0227] Also, certain embodiments provides the infrastructure necessary to
manage multiple simultaneously running collection procedures 70 on
different collection device 24 by different patients 12, while ensuring
secure web-based communication for receiving and transmitting the
collection procedures 70 and the results obtained from the analysis of
these collection procedures 70. For example, certain embodiments help the
clinician 14 by: making it easier for the clinician 14 to impact all of
the stages of a patient's therapy ranging from disease state
determination to regular monitoring under a working regular therapy;
making it possible for the clinician 14 to manage the various stages of
collection procedure 70 execution for a group of patients in a secure,
and web-based format; offering the clinician 14 flexibility by providing
the option to select collection procedures 70 from a pre-determined list
or modify a collection procedure 70 based on patient needs; making the
interaction between the clinician 14 and the patient 12 more effective as
the communication is entirely data-centric and guided by, for example, a
medical question at hand.

[0228] Specific examples of therapy optimization are described below,
specifically in the context of insulin titration.

[0229] Structured Collection Embodiments for Optimizing the Titration of
Insulin

[0230]FIG. 19A provides an exemplary embodiment of structured collection
protocols for optimizing the titration of insulin dosage, which thereby
yield dosages of insulin which maintain biomarker levels within a desired
range. In one embodiment, the titrated insulin may be basal insulin. Upon
starting the structured collection, the dosage of insulin is typically
the initial prescribed dosage, for example, the initial prescribed dosage
listed on the package. However, other dosages are contemplated depending
on what stage of the structured collection protocol, as the entry
criteria may be considered before every biomarker reading. Consequently,
the initial dosage may be an adjusted dosage above the initial prescribed
dosage, the maximum allowable dosage, or even the optimized dosage. It is
contemplated that the structured collection may be used to obtain the
optimized insulin value, or may be used post-optimization to verify that
the insulin dosage is still optimal.

[0231] In the embodiments of FIG. 19A, the structured collection protocols
may optionally require the consideration of entry criteria 710 before
beginning collection of the biomarker data. It is contemplated that the
diabetic person, the healthcare provider, or both may determine whether
the entry criteria are met. The entry criteria, which in some embodiments
may be established by the healthcare provider, may relate to the age,
weight, and medical history of the diabetic person. Consequently, the
structured collection protocol may require a diabetic person to receive a
check-up or physical to ensure the diabetic person satisfies the entry
criteria. For instance, the entry criteria may specify the fasting plasma
glucose (FPG) level or glycolated hemoglobin level as determined by the
HbA1c test. The normal range for the HbA1c test is between 4-6% for
people without diabetes, so the entry criteria may require values above
about 6%, or in exemplary embodiment, between about 7.5% to about 10%. As
an additional example of entry criteria, a fasting plasma glucose level
of at least about 140 mg/dl is required. The entry criteria may also set
requirements on weight or Body Mass Index (BMI). For example, the
required BMI may be greater than about 25 kg/m2, or between about 26
kg/m2 to about 40 kg/m2. Additionally, the entry criteria may specify a
desired age range (e.g., 30-70) or the number of years afflicted with
diabetes (e.g., at least 2 years). Moreover, while it is contemplated
that the structured collection protocol is applicable to persons
afflicted all types of diabetes, the entry criteria may limit the
structured collection protocol to type 2 diabetics. Furthermore, the
entry criteria may center on the current diabetes treatment regimen of
the diabetic person. For example, the entry criteria may require that the
treatment regimen for the diabetic person be limited to oral
anti-diabetes medication i.e., no injected insulin. Additionally, the
entry criteria may require that the diabetic person not be ill or under
stress. As stated above, while the embodiments of FIG. 19A are directed
to the consideration of entry criteria, the present structured collection
protocols do not require the consideration of entry criteria before
collection of biomarker data. For example, referring to the additional
embodiments of FIGS. 19B-D, the embodiment of FIG. 19B requires the
consideration of entry criteria; however, the embodiments of FIGS. 19C
and 19D do not include such constraints.

[0232] Referring again to FIG. 19A, if the entry criteria are not met, the
structured collection protocol will not be initiated 715. The diabetic
person or healthcare provider may determine whether the entry criteria
have been met, or the data processor may determine whether criteria have
been met. If the entry criteria are met 710, then the diabetic person may
commence with the structured collection protocol. However, in some
embodiments, it may be required for the diabetic person satisfy adherence
criteria before the collection of biomarkers or the administration of
insulin.

[0233] The adherence criteria are the procedural requirements that the
diabetic person must follow when conducting the structured collection
protocol. To get a proper baseline for the biomarker readings, it may be
beneficial to ensure all readings are taken uniformly, i.e., at
approximately the same time of day for each sampling instance.
Consequently, the adherence criteria may specify that biomarker
collection or insulin administration be conducted at the same time each
day. To aid the diabetic person in satisfying the adherence criteria, the
data processor display prompt the diabetic patient with audio and/or
visual reminders to collect their biomarker sample, and enable the
diabetic patient to set future reminders. In specific embodiments, the
adherence criteria may also require that the diabetic person fast for a
set period of time prior to collecting the biomarker reading. The
adherence criteria may also be directed to determining whether the
diabetic person is taking the correct dosage of insulin. In additional
embodiments, the adherence criteria may also require no recent
hypoglycemic events or severe hypoglycemic events (low blood glucose
events) a set period (e.g. one week) before the collection of biomarker
data. Furthermore, the adherence criteria may specify an exercise regimen
or eating regimen for the diabetic person. As used herein, "eating
regimen" means the typical eating regimen of the diabetic person in terms
of calories, carbohydrate intake and protein intake.

[0234] If the diabetic person fails to meet any or all of the adherence
criteria, the diabetic person may be informed, for example, by the
display of the blood glucose meter that they failed to meet the adherence
criterion. If the diabetic person fails to meet the adherence criteria,
the data processor device may tag the adherence event or the diabetic
person may record the occurrence of the adherence event. After the
adherence event is recorded, the structured collection protocol is
typically continued. However, if too many adherence events are recorded
(e.g., more than 4 within a sample period, more than 20 adherence events
within the entirety of execution), then the structured collection
protocol may be terminated. Furthermore, the structured collection
protocol may also evaluate adherence events differently. For example,
there may be a tiered adherence event assessment, wherein adherence
events are weighted. In one or more embodiments, if the adherence event
does not impact the biomarker data, then it is not weighted as heavily as
an adherence event that affects the biomarker data. For example, when a
diabetic person fasts the requisite time period before taking a fasting
blood glucose reading, but fails to record that the reading is a fasting
blood glucose reading, this would be categorized diabetic as a less
significant and thereby lower weighted adherence event, because the
recording error does not affect the fasting blood glucose reading. In
contrast, fasting less than the requisite period will impact the fasting
blood glucose reading, and thus constitutes a more significant and
thereby higher weighted adherence event.

[0235] If there is a violation event (e.g., a missed insulin
administration), the structured collection protocol is more likely to be
terminated than for an adherence event (e.g., fasting less than the
required fasting period), because a violation event impacts the
structured collection protocol more significantly. Since the present
structured collection protocol is directed to optimizing insulin
administration, it stands to reason that missing an insulin dose would be
a significant violation event.

[0236] Like other instructions provided to the diabetic person throughout
the structured collection protocol, the entry criteria or the adherence
criteria may be provided to the diabetic person via a paper instruction
form, or a display unit on a data processing device or processor 102 as
shown in FIG. 3. The data processing devices may be any electronic device
described above. In one or more embodiments, the data processing device
may be a computer or a blood glucose meter with a data processor and
memory units therein. In addition to listing the entry criteria,
adherence criteria, or both, the data processing device may prompt the
diabetic person to answer medical questions, wherein the answers to the
medical questions are used by the device to determine compliance with the
entry criteria, or adherence criteria. The data processing device may
inform the diabetic person of the failure to comply with the entry
criteria or adherence criteria. For example, the data processing device
may inform a diabetic person if subsequent sampling instances are not
taken around the same time as the first sampling instance. The patient
can record sampling instances or answer medical questions by entering the
data event directly into a device or computer, wherein the processor 102
can store the information and provide additional analysis depending on
the parameters of the structured collection protocol.

[0237] Referring again to FIG. 19A, the diabetic person may begin
collection of one or more sampling sets of biomarker data. Each sampling
set comprises a sufficient plurality of non-adverse sampling instances
recorded over a collection period, which means at least two sampling
instances which are not indicative of an adverse event e.g., a
hypoglycemic or hyperglycemic event. Each sampling instance 740 comprises
a biomarker reading at a single point in time. The collection period for
the sampling set may be defined as multiple sampling instances within a
day, multiple sampling instances within a week, multiple sampling
instances within consecutive weeks, or multiple sampling instances on
consecutive days within a week. The biomarker may relate to the levels of
glucose, triglycerides, low density lipids, and high density lipids. In
one exemplary embodiment, the biomarker reading is a blood glucose
reading. In addition to the biomarker reading, each sampling instance may
comprise the biomarker reading and other contextual data associated with
the biomarker reading, wherein the contextual data is selected from the
group consisting of the time of collection, the date of collection, the
time when the last meal was consumed, affirmation that fasting has
occurred for the requisite period, and combinations thereof. In the
exemplary embodiment of FIG. 19B, the structured collection protocol
occurs over a 7 day method which requires the diabetic patient to
administer insulin in the evening followed by the collection of fasting
blood glucose reading the following morning. In addition to the morning
biomarker collection, the diabetic patient may also be instructed to take
an additional biomarker reading when the diabetic person is encountering
the symptoms of hypoglycemia.

[0238] Referring again to FIG. 19A, upon collecting the biomarker reading,
there is a determination as to whether the biomarker reading indicates an
adverse event 750. While the present discussion of adverse events centers
on hypoglycemic events and severe hypoglycemic events, which may
necessitate medical assistance, it is contemplated that the adverse
events may refer to undesirable levels of other biomarkers or medical
indicators, e.g., lipids levels, blood pressure levels, etc. In one
embodiment, this determination of adverse events may be performed by
comparing the biomarker reading to a low threshold, for example, the
hypoglycemic event or severe hypoglycemic event thresholds shown in Table
1 below. If the biomarker reading is below one or both of these
thresholds, then an adverse event may have occurred, and should be
recorded as an adverse event, or specifically recorded as a hypoglycemic
event or severe hypoglycemic event. As described above, this
determination may be performed by a data processor unit, or may be
entered manually by the diabetic person.

[0239] If there is an adverse event (e.g., a severe hypoglycemic event),
in one embodiment, the instructions or data processing device may
recommend that the diabetic person contacts their health care provider.
In another embodiment, the system may automatically contact the health
care provider (HCP). In addition, an adverse event may optionally lead to
a dosage reduction. Referring to Table 1 above, if it is a hypoglycemic
event (between 56-72 mg/dl), the HCP may be contacted 850, but the dosage
is not adjusted (See FIG. 19A). However, if it is a severe hypoglycemic
event (below 56 mg/dl), the dosage may be reduced by some amount (640),
for example, 2 units, 4 units, or another amount as dictated by the low
biomarker reading. In specific embodiments, if the recorded adverse event
is a second measured severe hypoglycemic event within the same day, the
dosage is not reduced. In further embodiments, a data processing device
may utilize an algorithm to automatically reduce the insulin dosage and
instruct the diabetic person of the reduced insulin dosage. Moreover, the
data processing device which collects the biomarker reading may
automatically notify a healthcare provider of the adverse event, for
example, by an automated email or text message.

[0240] If the biomarker reading is not adverse, the next step depends on
whether or not the sampling set 760 has a sufficient number of
non-adverse sampling instances. If only one sampling instance is required
for the sampling set, then the biomarker sampling parameter may be
calculated at that point; however, as stated above, the sampling set
typically requires a plurality or at least two sampling instances for
each sampling set. In exemplary embodiments, two or more sampling
instances taken on consecutive days are required for each sampling set.
If multiple sampling instances are required, then the diabetic person
must continue to collect sampling instances.

[0241] Once the requisite number of sampling instances for the sampling
set is obtained, the biomarker sampling parameter may be obtained 770.
The biomarker sampling parameter may be determined by various algorithms
or methodologies. For example, it may be determined by averaging sampling
instances, summing the sampling instances, performing a graphical
analysis on the sampling instances, performing a mathematical algorithm
on the sampling set, or combinations thereof. In an exemplary embodiment,
sampling instances (i.e., biomarker readings) are collected on at least
three consecutive days, and the average of the three consecutive days is
the biomarker sampling parameter.

[0242] After the biomarker sampling parameter is obtained, the value is
compared to a target biomarker range. As used herein, the target
biomarker range means an acceptable range of biomarker in the diabetic
person, which thereby demonstrates that the insulin is producing the
desired physiological response. If the biomarker sampling parameter falls
outside of the target biomarker range, then an insulin adjustment
parameter may be calculated 790. The insulin adjustment parameter is
associated with and computed from the biomarker sampling parameter.
Various methodologies and algorithms are contemplated for calculating the
insulin adjustment parameter. For example, the insulin adjustment
parameter may be computed by locating the insulin adjustment parameter
associated with the biomarker parameter in an insulin adjustment
parameter lookup table (See Table 1 above). As shown above in the
exemplary insulin adjustment parameter lookup table of Table 1, there may
be multiple tiers which dictate how much the insulin dosage should be
adjusted. For example, a fasting glucose level below 100 mg/dl but above
56 mg/dl will necessitate no adjustment to the insulin dosage. The
greater the deviation from the target range, the higher the adjustment of
insulin in units.

[0243] After determining the insulin adjustment parameter, the insulin
dosage may be adjusted by the amount of the insulin adjustment parameter,
as long as the insulin adjustment does not raise the insulin dosage above
the maximum allowable dosage. The adjusted insulin dosage cannot exceed a
maximum level set by the healthcare provider. Upon determining the
adjusted insulin dosage value, the diabetic person may then be instructed
to collect at least one additional sampling set at the adjusted insulin
dosage per the above described collection procedures. The biomarker
sampling parameter, the insulin adjustment parameter, and the adjusted
insulin dosage may be computed manually by the diabetic person or via a
data processing device.

[0244] If the biomarker sampling parameter is within a target biomarker
range, there is no adjustment of the insulin dosage. Moreover, the
insulin dosage may be considered optimized depending on other applicable
criteria. Specifically, an insulin dosage may be considered optimized if
one biomarker sampling parameter is within a target biomarker range, or
it may be considered optimized if at least two consecutive biomarker
sampling parameters are within a target biomarker range 820. If the
optimization definition requires at least two consecutive biomarker
sampling parameters within a target biomarker range, the diabetic person
is then instructed to collect at least one additional sampling set at the
adjusted insulin dosage per the above described collection procedures.
After the insulin dosage is considered optimized, the diabetic person is
instructed to exit the structured collection protocol. After exiting the
structured collection protocol 730, the diabetic person may conduct
further structured collection protocols to determine the future efficacy
of the optimized dosage.

[0245] In alternative embodiments, the diabetic patient may be instructed
to exit the structured collection protocol 730 if the diabetic person has
been undergoing the testing procedure for a long period, for example, 6
months or longer. Additionally, as described above, if there are multiple
adherence or violation events, then the test may be automatically
terminated by the data processing device or the diabetic patient may be
instructed to exit the structured collection protocol.

[0246] Classification Based on Adherence Criteria

[0247] In further embodiments, the structured collection procedures or
protocol may utilize classifications of sampling instances in a sampling
set in order to optimize the structured collection protocol. As described
above, the structured collection protocol may comprise various
calculations directed to assessment of a disease or therapy, the
optimization of a therapy, or combinations thereof. In one embodiment,
the structured collection protocol may be the insulin titration and
optimization processes described above. The structured collection
protocol may be performed on a collection device as described above,
wherein the collection device may comprise a meter configured to measure
one or more selected biomarkers, a processor disposed inside the meter
and coupled to memory, wherein the memory comprises collection
procedures, and software for the processor to execute.

[0248] Referring to FIG. 20, the user or diabetic patient begins the
structured collection protocol 900 by collecting one or more sampling
sets of biomarker data using the collection device 905, wherein each
sampling set comprises a sufficient plurality of sampling instances
recorded over a collection period. Each sampling instance includes a
biomarker reading. In one embodiment, the processor may require the
sampling instances to be non-adverse i.e., there are no biomarker
readings indicative of hypoglycemia or hyperglycemia. For each sample,
the processor may determine whether there is compliance with adherence
criteria 915. Noncompliance with adherence criteria is recorded as an
adherence event.

[0249] Referring to FIG. 20, either before or after collection, each
sampling instance may be classified using the processor 920, 930. The
samples may be classified as primary or secondary samples. Primary
samples 925 are sampling instances intended to be utilized preferably in
calculations performed by the processor that yield therapy results (e.g.,
adjusted insulin dosage amounts) for a diabetic person. As used herein,
"therapy results" are metrics, data, contextual information yielded from
the calculations performed in the structured collection protocol, wherein
the structured collection protocol is directed to disease status
assessment, therapy assessment, therapy optimization (e.g., insulin
titration), or combinations thereof. As described above, primary samples
may be construed as critical events, which should not be missed when
conducting the structured testing protocol; however, they can be replaced
with other samples. Secondary samples preferably are non-critical
sampling instances not intended to be utilized in calculations performed
by the processor that yield therapy results for a diabetic person 930,
940 unless the secondary samples are promoted to primary samples as
described below. Regardless of whether samples are classified as primary
or secondary, all sampling instances may be utilized in identifying
adverse events, or measurement issues associated with the biomarker
readings.

[0250] In further embodiments, it is contemplated to have additional
classifications. For example, sampling instances may be classified as
tertiary samples. Tertiary samples 935 are samples which cannot be
promoted to primary samples as a replacement for another primary sample.
While adherence is considered for tertiary samples, these values have no
impact on the structured collection protocol. For example, but not by way
of limitation, tertiary samples are sampling instances used for safety
checks, as spacers to maintain a consistent sampling interval, or as
input to visual presentations of reported data. It is contemplated to
have further classifications in addition to primary, secondary, and
tertiary. Like the primary and secondary samples, the tertiary samples
may still be utilized to identify adverse events.

[0251] Referring to FIG. 20, for primary samples without corresponding
recorded adherence events, the user may simply continue the protocol 955,
or optionally determine if there are a sufficient number of primary
samples in the sampling set, which have complied with adherence
criterion.

[0252] For primary samples with corresponding recorded adherence events
945, the processor may determine which further action 960 or additional
task is appropriate. While it is contemplated to terminate the protocol
in light of adherence events, the embodiments of the present invention
focus on compensating for these adherence events while continuing the
performance of the structured collection protocol. The processor includes
algorithms that calculate which additional task should be performed based
on numerous factors. The algorithm may consider the contextual
information for the sampling instances, the number of sampling instances,
the classification of the sampling instances, the adherence of the
sampling instances, and various other contemplated factors. Based on
these factors, the algorithm selects the additional task most suitable
for continuing the structured collection protocol

[0253] In one embodiment, the processor may consider whether the sampling
set has the requisite number of primary samples 965, without
corresponding recorded adherence events. If so, the processor may perform
the additional task of ignoring these primary samples with corresponding
recorded adherence events and performing the calculations using primary
samples, which do not include corresponding recorded adherence events, in
order to obtain therapy results 985. Referring to FIG. 20, if the desired
results of the protocol are achieved 990 (e.g., the insulin dosage is
optimized), the user may be instructed to end the protocol 970.

[0254] Alternatively, if there are not a sufficient number of primary
samples without recorded adherence events in the sampling set, the
collection device may consider whether there are secondary samples which
are suitable replacements for the primary sample 995. In this case, if
there are secondary samples, which do not have corresponding recorded
adherence events, these secondary samples may be promoted to primary
samples and may replace the primary samples with associated adherence
events 980. In another exemplary embodiment, the replacement of the
primary samples may be performed automatically via the processor. When
replacing a primary sample with a secondary sample, the processor may
require that the primary sample and the secondary sample be part of the
same sampling set. Moreover, when replacing a primary sample with a
secondary sample, the processor may also require that the secondary
sample comprise the same, substantially identical, partially identical or
similar contextual information or metric as the primary sample to be
replaced. For example, the processor may replace a primary fasting blood
glucose level with a secondary fasting blood glucose level since the
primary and secondary samples would have the same metric. In contrast,
the processor would not replace a primary fasting blood glucose level
with a secondary insulin to carbohydrate reading because the metrics i.e.
contextual information is not the same. Unlike primary samples, adherence
events for secondary samples may not require any further action or
additional tasks to be performed (e.g. replacement); however, recorded
adherence events may render a secondary sample unsuitable for a
replacement for a primary sample 950. If there are no suitable
replacement samples, for example, due to adherence events, the collection
device may instruct the user to collect at least one additional sampling
instance 1000 to be used as a primary sample in the structured collection
protocol. In another embodiment, the processor may instruct the diabetic
person to restart the sampling set 1005, without first terminating the
protocol.

[0255] While the embodiments of the present invention are primarily
focused on extending the structured collection protocol to compensate for
primary samples with adherence events, the processor may, in some
embodiments, instruct the user to end the protocol 970, because of the
adherence event. Alternatively, the user may be instructed to contact a
healthcare provider 975. It is contemplated that the user may be
instructed to both end the protocol and contact the healthcare provider.

[0256] To reiterate, the at least one additional task is calculated by the
processor if one or more sampling instances is recorded with a
corresponding recorded adherence event and the sampling instance is
classified as a primary sample. For example, if an adherence event is
recorded for a primary sample, the system may calculate a resulting task,
for example, replacing the primary sample by a secondary sample which
fulfills the adherence criteria. As a consequence, the secondary sample
is promoted as a primary sample.

[0257] However, if an adherence event for a secondary sample is recorded,
which might be the same adherence event as recorded for the primary
sample as exemplarily mentioned above, the resulting consequence that is
calculated by the system may be different. For example, the resulting
task may be to block that secondary sampling instance from further
calculation, and thereby preclude this secondary sample from being used
as a primary sample.

[0258] By dynamically calculating a task resulting from an adherence
event, the system facilitates the flexible handling of the structured
collection protocol. In particular, in case of an incorrect handling of
the protocol by the user or a detection of undesired value, the system
allows continuing the protocol so that the stored data is not wasted and
can be evaluated within the structured collection protocol. Based on one
or more embodiments, a differentiation between different classifications
of sampling instances is possible so that an adherence event can be
flexibly handled by the system. For example, adherence events for primary
samples should not be used in the calculations of the structured
collection protocol. However, adherence events for secondary samples are
primarily utilized in determining whether a secondary sample is suitable
as a primary sample, and do not require replacement of the secondary
sample in the sampling set. Moreover, adherence events for tertiary
samples are recorded; however, the tertiary samples are not utilized in
the calculations of the structured collection protocol.

[0259] The above described embodiments of the classification centered on
adherence generally; however, the embodiments of the present invention
may also encompass acceptance criteria, which are defined above as a
subset of adherence criteria. In one embodiment, the acceptance criteria
may require a biomarker reading to be within an expected range. In some
instances, a biomarker reading outside of the expected range may be
indicative of an adverse event. It is contemplated that the structured
collection protocol may compensate for this adverse event by utilizing
the procedures illustrated in FIG. 20.

[0260] Thus, by the above disclosure embodiments concerning a system and
method managing the execution, data collection, and data analysis of
collection procedures running simultaneously on a meter are disclosed.
One skilled in the art will appreciate that the teachings can be
practiced with embodiments other than those disclosed. The disclosed
embodiments are presented for purposes of illustration and not
limitation, and the invention is only limited by the claims that follow.